{"year":"2023","title":"''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Text","authors":["R Hada, A Seth, H Diddee, K Bali - arXiv preprint arXiv:2310.17428, 2023"],"snippet":"Language serves as a powerful tool for the manifestation of societal belief systems. In doing so, it also perpetuates the prevalent biases in our society. Gender bias is one of the most pervasive biases in our society and is seen in online and offline …","url":["https://arxiv.org/pdf/2310.17428"]}
{"year":"2023","title":"12 The Future of","authors":["P Chundi, V Bommanapally, V Gadhamshetty - Machine Learning in 2D Materials …, 2023"],"snippet":"… GPT-3 is an autoregressive model built with 96 layers [31], increased embedding vector dimension of 12888, trained with 175B parameters on five datasets including Common crawl, WebText2, Books1, Books2, and Wikipedia. Though GPT-3 has …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=vcrYEAAAQBAJ&oi=fnd&pg=PA217&dq=commoncrawl&ots=ECheeM6s-k&sig=7ob0zjXEaKZNMVUPtMJFlTgQIJ0"]}
{"year":"2023","title":"14 Augmenting and Informing the Translation Process through Workflow-Enabled CALT Tools","authors":["SM Rudan, E Kelbert, L Kovacevic, M Reynolds… - Computer-Assisted Literary …, 2023"],"snippet":"CALT is an emerging field in the process of defining itself, but it is already, we feel, a misnomer. Adding an ‘L’(Literary) to the pre-existing notion of Computer-Assisted Translation (CAT) creates continuity with CAT research; Machine Translation (MT) is …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=P13bEAAAQBAJ&oi=fnd&pg=PA258&dq=commoncrawl&ots=IYhfg3_tre&sig=NkpRTu0wMw5egO-e58ZBb2KiLs0"]}
{"year":"2023","title":"19. Assessing collective identity (non-) verification with social media data through web scraping, sentiment analysis, and qualitative coding","authors":["TP Love, JL Davis, RE Davis, WG Fisher, RM Barczak - Handbook of Research …, 2023"],"snippet":"… Perhaps the most prolific example of these techniques is Common Crawl, a non-profit organization that employs a web crawling and web scraping program to harvest information across the Internet. Common Crawl has been web crawling and web …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=0rHLEAAAQBAJ&oi=fnd&pg=PA261&dq=commoncrawl&ots=tWK4u0Huom&sig=wYMvXZZg4c53jdLKG8OSCDd_LRs"]}
{"year":"2023","title":"22 Forward Thinking on GeoAI","authors":["S Newsam - Handbook of Geospatial Artificial Intelligence, 2023"],"snippet":"… Second, is the unsupervised pre-training on large corpora of text such as the Common Crawl archive of the Internet. This pre-training does not require manually labeled data since it largely involves simply determining whether the model correctly …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=liXpEAAAQBAJ&oi=fnd&pg=PA427&dq=commoncrawl&ots=CO48Jg0Q06&sig=R9edTPxNRPHWUThKp3EEhieFIe4"]}
{"year":"2023","title":"3.3 On Information and Interactions on the Web","authors":["V Charpenay - Agents on the Web"],"snippet":"… In natural language processing, large language models such as BERT or GPT are trained on large corpi found on the Web, including Wikipedia and CommonCrawl 4 data. … php 4 https://commoncrawl. org/ 5 https://pedantic-web. org/ …","url":["https://drops.dagstuhl.de/opus/volltexte/2023/19182/pdf/dagrep_v013_i002_p071_23081.pdf#page=10"]}
{"year":"2023","title":"6 Author-Tailored Neural Machine Translation Systems for Literary Works","authors":["A Oliver - Computer-Assisted Literary Translation, 2023"],"snippet":"Literature is one of the areas where machine translation (MT) has not been used until very recent times. Nevertheless, the impressive increase in quality obtained with neural machine translation (NMT) systems has led some authors to start …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=P13bEAAAQBAJ&oi=fnd&pg=PA126&dq=commoncrawl&ots=IYhfg3_tre&sig=TRar6iD7Fq7PUah62jFiPmhOQuM"]}
{"year":"2023","title":"6 Distributed computational models of intervention effects: A study on cleft structures in French","authors":["G Samo, P Merlo - It-Clefts: Empirical and Theoretical Surveys and …, 2023"],"snippet":"… Briefly, the uncompressed 270 GB of French text corpus consists of 24 sub-corpora gathered from different sources,(eg Wikipedia and books, random text crawled from the Internet (eg Common Crawl). 6 We use the code discussed in Renaud (2020) …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=WLbiEAAAQBAJ&oi=fnd&pg=PA157&dq=commoncrawl&ots=XupU0tqLh2&sig=fuFlpLZq-Un0elMSOiWBllsnaPI"]}
{"year":"2023","title":"6 Persian Named Entity Recognition with Structural Prediction Methods","authors":["H Poostchi, M Piccardi - Persian Computational Linguistics and NLP, 2023"],"snippet":"… As the standard word embedding we have downloaded and used the 300D Farsi fastText embeddings trained on Common Crawl and … Our initial experiments showed that the combination of the fastText embeddings trained on Common Crawl …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=mmu8EAAAQBAJ&oi=fnd&pg=PA149&dq=commoncrawl&ots=IT4Mfr3GhG&sig=SGTXp5guThr4EXwAn-KvibAk5yc"]}
{"year":"2023","title":"\" Get a Higher Return on Your Savings!\": Comparing Adverts for Cryptocurrency Investment Scams Across Platforms","authors":["GA Siu, A Hutchings - 2023 IEEE European Symposium on Security and …, 2023"],"snippet":"This work compares machine learning methods using supervised, semi-supervised and unsupervised learning, to classify advertisements for cryptocurrency related investment scams found in the online forum Bitcointalk, and the social media …","url":["https://www.computer.org/csdl/proceedings-article/eurospw/2023/272000a158/1OFtfhsKFVu"]}
{"year":"2023","title":"\" I wouldn't say offensive but...\": Disability-Centered Perspectives on Large Language Models","authors":["V Gadiraju, S Kane, S Dev, A Taylor, D Wang… - 2023"],"snippet":"Large language models (LLMs) trained on real-world data can inadvertently reflect harmful societal biases, particularly toward historically marginalized communities. While previous work has primarily focused on harms related to age and race …","url":["https://research.google/pubs/pub52358.pdf"]}
{"year":"2023","title":"\" Kelly is a Warm Person, Joseph is a Role Model\": Gender Biases in LLM-Generated Reference Letters","authors":["Y Wan, G Pu, J Sun, A Garimella, KW Chang, N Peng - arXiv preprint arXiv …, 2023"],"snippet":"… 2019a), which is sourced from online biographies in the Common Crawl corpus. The dataset also includes metadata across several occupations and gender indicators. We prompt ChatGPT to rephrase this initial biography into two versions …","url":["https://arxiv.org/pdf/2310.09219"]}
{"year":"2023","title":"\" Paraphrasing The Original Text\" Makes High Accuracy Long-Context QA","authors":["Y Yu - arXiv preprint arXiv:2312.11193, 2023"],"snippet":"Although LLMs continue to iterate and improve, most open-source models still have a context window of no more than 4k, limiting their ability to handle long-context problems. Most existing open-source models for long-context chat still lack …","url":["https://arxiv.org/pdf/2312.11193"]}
{"year":"2023","title":"\\texttt {IngesTables}: Scalable and Efficient Training of LLM-Enabled Tabular Foundation Models","authors":["S Yak, Y Dong, J Gonzalvo, S Arik - NeurIPS 2023 Second Table Representation …, 2023"],"snippet":"There is a massive amount of tabular data that can be taken advantage of via `foundation models' to improve prediction performance for downstream tabular prediction tasks. However, numerous challenges constitute bottlenecks in building tabular foundation …","url":["https://openreview.net/pdf?id=EocsZtcA7P"]}
{"year":"2023","title":"Özgeçmişlerde varlık isimlerinin tanınması Named entity recognition in resumes","authors":["E Kesim, S Tanberk - 2023 Innovations in Intelligent Systems and …, 2023"],"snippet":"Named entity recognition (NER) is used to extract information from various documents and texts such as names and dates. It is important to extract education and work experience information from resumes in order to filter them. Considering …","url":["https://ieeexplore.ieee.org/abstract/document/10296807/"]}
{"year":"2023","title":"“Source?”“I Made It Up”: The Ethics of Citing ChatGPT in Academia","authors":["C DeKay - 2023"],"snippet":"… This should not be necessarily surprising as we do know that most LLMs are trained using the CommonCrawl dataset, a collection of twelve years’ worth of publicly available Internet pages, where sites like AO3 with over 11 million freely …","url":["https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=1009&context=fims_evolvingtech_finalproj_summer2023"]}
{"year":"2023","title":"A Benchmark Analysis of Few-Shot Biomedical Named Entity Recognition","authors":["M Postiglione, I Iodice"],"snippet":"… This led to the development of pretrained systems such as BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer), which were trained with large language datasets, such as Wikipedia …","url":["https://picuslab.dieti.unina.it/images/pdfs/_TESI__IVANO_IODICE.pdf"]}
{"year":"2023","title":"A benchmark for evaluating Arabic contextualized word embedding models","authors":["A Elnagar, S Yagi, Y Mansour, L Lulu, S Fareh - Information Processing & …, 2023"],"snippet":"… It was pre-trained on a 2.5 TB of clean CommonCrawl dataset in 100 languages. … Amassing huge amounts of non-financial data as in the Common Crawl dilutes the patterns found in financial texts. That is the most likely explanation for why so many …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323001899"]}
{"year":"2023","title":"A Benchmark for Text Expansion: Datasets, Metrics, and Baselines","authors":["Y Chen, H Jiang, W Bi, R Wang, L Wang, S Shi, R Xu - arXiv preprint arXiv …, 2023"],"snippet":"… We use CommonCrawl2 as the data source. Based on the four complementary approaches in §3, we further conduct data filtering (Appendix D) and construct a large-scale TE corpus with 12M pairs for both English and Chinese. Detailed …","url":["https://arxiv.org/pdf/2309.09198"]}
{"year":"2023","title":"A benchmark for toxic comment classification on Civil Comments dataset","authors":["C Duchene, H Jamet, P Guillaume, R Dehak - arXiv preprint arXiv:2301.11125, 2023"],"snippet":"Toxic comment detection on social media has proven to be essential for content moderation. This paper compares a wide set of different models on a highly skewed multi-label hate speech dataset. We consider inference time and several metrics to …","url":["https://arxiv.org/pdf/2301.11125"]}
{"year":"2023","title":"A BERT-Based Model for Financial Social Media Sentiment Analysis","authors":["J Delgadillo, J Kinyua, C Mutigwe - International Journal of Cognitive and Language …, 2023"],"snippet":"The purpose of sentiment analysis is to determine the sentiment strength (eg, positive, negative, neutral) from a textual source for good decision-making. Natural Language Processing (NLP) in domains such as financial markets requires …","url":["https://publications.waset.org/10012944/a-bert-based-model-for-financial-social-media-sentiment-analysis"]}
{"year":"2023","title":"A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development","authors":["T Wu, S He, J Liu, S Sun, K Liu, QL Han, Y Tang - IEEE/CAA Journal of Automatica …, 2023"],"snippet":"ChatGPT, an artificial intelligence generated content (AIGC) model developed by OpenAI, has attracted world-wide attention for its capability of dealing with challenging language understanding and generation tasks in the form of …","url":["https://www.ieee-jas.net/en/article/doi/10.1109/JAS.2023.123618"]}
{"year":"2023","title":"A Case Study Analysis of Google Smart Compose and Its Effects on the Student Writing Process From the Student and Teacher Perspectives","authors":["H Bryant - 2023"],"snippet":"This qualitative case study addresses the rise in popularity of the use of predictive text programs within the K-12 educational environment. A problem exists in the discrepancy between the widespread availability of Google Smart Compose within …","url":["https://search.proquest.com/openview/f62cdbf5839f7b94d7eaf8f39e8cdf1a/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"A Cohesive Distillation Architecture for Neural Language Models","authors":["JP Wahle - arXiv preprint arXiv:2301.08130, 2023","LR Terry - 2023"],"snippet":"A recent trend in Natural Language Processing is the exponential growth in Language Model (LM) size, which prevents research groups without a necessary hardware infrastructure from participating in the development process. This study …","url":["https://arxiv.org/pdf/2301.08130","https://www.authorea.com/doi/pdf/10.22541/au.167528147.79728645"]}
{"year":"2023","title":"A Comparative Performance Evaluation of Algorithms for the Analysis and Recognition of Emotional Content","authors":["K Kyritsis, N Spatiotis, I Perikos, M Paraskevas - 2023"],"snippet":"Sentiment Analysis is highly valuable in Natural Language Processing (NLP) across domains, processing and evaluating sentiment in text for emotional understanding. This technology has diverse applications, including social media monitoring, brand …","url":["https://www.intechopen.com/online-first/87923"]}
{"year":"2023","title":"A Comparative Study of Code Generation using ChatGPT 3.5 across 10 Programming Languages","authors":["A Buscemi - arXiv preprint arXiv:2308.04477, 2023"],"snippet":"… OpenAI employed a dataset known as the Common Crawl [24], a publicly accessible collection of billions of web pages, making it as one of the most extended text databases currently accessible. It is to be noted that the selection of the dataset …","url":["https://arxiv.org/pdf/2308.04477"]}
{"year":"2023","title":"A Comparative Study of Pre-trained Language Models to Filter Informative Code-mixed Data on Social Media during Disasters","authors":["H Salemi, Y Senarath, H Purohit"],"snippet":"… A multi-lingual language model trained using masked language modeling on 2.5 TB of newly created and cleaned CommonCrawl data. … XLM-R: A multilingual version of RoBERTa that is pre-trained on 2.5TB of filtered CommonCrawl data …","url":["https://idl.iscram.org/files/salemi/2023/2576_Salemi_etal2023.pdf"]}
{"year":"2023","title":"A Comparative Study of Sentence Embedding Models for Assessing Semantic Variation","authors":["DM Mistry, AA Minai - arXiv preprint arXiv:2308.04625, 2023"],"snippet":"… XLM-R [14] is a transformer trained using masked language modeling on one hundred languages using over two terabytes of filtered CommonCrawl data. The trained model shows significant performance improvement over multilingual BERT (mBERT) …","url":["https://arxiv.org/pdf/2308.04625"]}
{"year":"2023","title":"A Comparative Study of Text Embedding Models for Semantic Text Similarity in Bug Reports","authors":["A Patil, K Han, S Mukhopadhyay - arXiv preprint arXiv:2308.09193, 2023"],"snippet":"… For Fasttext, we employed the ”crawl-300d2M-subword” model, which consisted of 2 million word vectors trained with subword information on the Common Crawl dataset, encompassing 600 billion tokens. In the case of Doc2Vec, we used the ”GoogleNews-vectors-negative300…","url":["https://arxiv.org/pdf/2308.09193"]}
{"year":"2023","title":"A Comparative Study of Text Representations for French Real-Estate Classified Advertisements Information Extraction","authors":["L Cadorel, AGB Tettamanzi - 2023"],"snippet":"Text representations are widely used in NLP tasks such as text classification. Very powerful models have emerged and been trained on huge corpora for different languages. However, most of the pre-trained models are domain-agnostic and fail …","url":["https://ceur-ws.org/Vol-3495/paper_06.pdf"]}
{"year":"2023","title":"A Comparative Study of Transformer Based Pretrained AI Models for Content Summarization","authors":["ASA Rasheed, MM Masud, M Abduljabbar - 2023 15th International Conference on …, 2023"],"snippet":"In this study, we examine different transformer based pretrained Artificial Intelligence (AI) models on their ability to summarize text content from different sources. AI has emerged as a powerful tool in this context, offering the potential to automate and …","url":["https://ieeexplore.ieee.org/abstract/document/10366411/"]}
{"year":"2023","title":"A Comparitive Study on Abstractive Text Summarization Techniques Using Deep Learning (ATS-DL)","authors":["S Adhithyan, AR Nirupama, S Sri Akshya… - Soft Computing: Theories …, 2023"],"snippet":"… It is trained using Common Crawl’s web crawl corpus (C4), a very large corpus of data for all NLP tasks. T5 comes in 5 variants such as T5-small, T5-big, T5-large, T5-3B and T5-11B, where each is trained with 60 million, 220 million, 770 million, 3 billion …","url":["https://link.springer.com/chapter/10.1007/978-981-19-9858-4_80"]}
{"year":"2023","title":"A compendium of data sources for data science, machine learning, and artificial intelligence","authors":["P Bilokon, O Bilokon, S Amen - arXiv preprint arXiv:2309.05682, 2023"],"snippet":"Recent advances in data science, machine learning, and artificial intelligence, such as the emergence of large language models, are leading to an increasing demand for data that can be processed by such models. While data sources are application-specific …","url":["https://arxiv.org/pdf/2309.05682"]}
{"year":"2023","title":"A Comprehensive Analysis of the Effectiveness of Large Language Models as Automatic Dialogue Evaluators","authors":["C Zhang, LF D'Haro, Y Chen, M Zhang, H Li - arXiv preprint arXiv:2312.15407, 2023"],"snippet":"Automatic evaluation is an integral aspect of dialogue system research. The traditional reference-based NLG metrics are generally found to be unsuitable for dialogue assessment. Consequently, recent studies have suggested various unique …","url":["https://arxiv.org/pdf/2312.15407"]}
{"year":"2023","title":"A Comprehensive Overview of Large Language Models","authors":["H Naveed, AU Khan, S Qiu, M Saqib, S Anwar… - arXiv preprint arXiv …, 2023"],"snippet":"… The dataset is extracted from the public common crawl scrape. The model uses GeGLU activation and trains with a vocab size of 250,000 … 3) PanGu-α [78]: An autoregressive model trained on 1.1TB Chinese data collected from Common Crawl …","url":["https://arxiv.org/pdf/2307.06435"]}
{"year":"2023","title":"A Comprehensive Study of ChatGPT: Advancements, Limitations, and Ethical Considerations in Natural Language Processing and Cybersecurity","authors":["M Alawida, S Mejri, A Mehmood, B Chikhaoui… - Information, 2023"],"snippet":"This paper presents an in-depth study of ChatGPT, a state-of-the-art language model that is revolutionizing generative text. We provide a comprehensive analysis of its architecture, training data, and evaluation metrics and explore its …","url":["https://www.mdpi.com/2078-2489/14/8/462"]}
{"year":"2023","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","authors":["Y Cao, S Li, Y Liu, Z Yan, Y Dai, PS Yu, L Sun - arXiv preprint arXiv:2303.04226, 2023"],"snippet":"Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its …","url":["https://arxiv.org/pdf/2303.04226"]}
{"year":"2023","title":"A Comprehensive Survey of ChatGPT: Advancements, Applications, Prospects, and Challenges","authors":["A Nazir, Z Wang - Meta-Radiology, 2023"],"snippet":"Large Language Models (LLMs) especially when combined with Generative Pre-trained Transformers (GPT) represent a groundbreaking in natural language processing. In particular, ChatGPT, a state-of-the-art conversational language model with a user-friendly …","url":["https://www.sciencedirect.com/science/article/pii/S295016282300022X"]}
{"year":"2023","title":"A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks","authors":["S Islam, H Elmekki, A Elsebai, J Bentahar, N Drawel… - arXiv preprint arXiv …, 2023"],"snippet":"Transformer is a deep neural network that employs a self-attention mechanism to comprehend the contextual relationships within sequential data. Unlike conventional neural networks or updated versions of Recurrent Neural Networks (RNNs) such as …","url":["https://arxiv.org/pdf/2306.07303"]}
{"year":"2023","title":"A Computational Analysis on the Role of Social Relationships in Online Communication and Information Diffusion","authors":["M Choi - 2023"],"snippet":"… 2014] embeddings with 300 dimensions, trained on the Common Crawl corpus (42B tokens) performed best in the tasks we addressed. In addition to considering a word’s local context, GloVe uses also global co-occurrence statistics across the whole text …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/177746/minje_1.pdf?sequence=1"]}
{"year":"2023","title":"A Conversational Breakdown Detector for a Motivational Interviewing Conversational Agent","authors":["ZL Qin - The iJournal: Student Journal of the University of …, 2023"],"snippet":"… The first is pre-training a large language model on a general corpus, such as Wikipedia or Common Crawl. The next step is adding a classification layer and fine-tuning the model on new data so this model can be used in downstream tasks. They …","url":["https://theijournal.ca/index.php/ijournal/article/download/42237/32259"]}
{"year":"2023","title":"A Cross-Attention Augmented Model for Event-Triggered Context-Aware Story Generation","authors":["C Tang, T Loakman, C Lin - arXiv preprint arXiv:2311.11271, 2023"],"snippet":"Despite recent advancements, existing story generation systems continue to encounter difficulties in effectively incorporating contextual and event features, which greatly influence the quality of generated narratives. To tackle these …","url":["https://arxiv.org/pdf/2311.11271"]}
{"year":"2023","title":"A Data-driven Understanding of Left-Wing Extremists on Social Media","authors":["U Balcı, M Sirivianos, J Blackburn - arXiv preprint arXiv:2307.06981, 2023"],"snippet":"Social media's role in the spread and evolution of extremism is a focus of intense study. Online extremists have been involved in the spread of online hate, mis/disinformation, and real-world violence. However, the overwhelming majority of existing work has …","url":["https://arxiv.org/pdf/2307.06981"]}
{"year":"2023","title":"A Dataset and Strong Baselines for Classification of Czech News Texts","authors":["H Kydlíček, J Libovický - arXiv preprint arXiv:2307.10666, 2023"],"snippet":"… We create the CZE-NEC by crawling Czech news websites from CommonCrawl (§ 2.1) and use the available metadata to define classification tasks (§ 2.3). … Instead of crawling the pages directly, we used the CommonCrawl archive to extract the articles. …","url":["https://arxiv.org/pdf/2307.10666"]}
{"year":"2023","title":"A deep learning framework for the detection of Malay hate speech","authors":["K Maity, S Bhattacharya, S Saha, M Seera - IEEE Access, 2023"],"snippet":"Although social media can efficiently disseminate information, they also facilitate the dissemination of online abuse, harassment, and hate speech. In 2019, United Nations Secretary-General introduced the United Nations Strategy and Plan of …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10192900.pdf"]}
{"year":"2023","title":"A Deep Learning-Based Phishing Detection System Using CNN, LSTM, and LSTM-CNN","authors":["Z Alshingiti, R Alaqel, J Al-Muhtadi, QEU Haq… - Electronics, 2023"],"snippet":"… Around one million legitimate and phishing URLs were used on the dataset collected from PhishTank and Common Crawl. To build the IPDS, the LSTM and CNN classifier used over 10,000 images and one million URLs for training. The …","url":["https://www.mdpi.com/2046874"]}
{"year":"2023","title":"A Deep Neural Network Architecture for Extracting Contextual Information","authors":["Z Alami Merrouni, B Frikh, B Ouhbi - The 3rd International Conference on Artificial …, 2023"],"snippet":"… However, existing datasets for AKE are quite small, so we use Stanford's GloVe Embeddings, which are trained on either Wikipedia 2014 + Gigaword 5 (approximately 6 billion tokens) or Common Crawl (approximately 6 billion tokens) (about 840 …","url":["https://link.springer.com/chapter/10.1007/978-3-031-27762-7_10"]}
{"year":"2023","title":"A deep neural network-based data-driven model for evaluating the recognition of ADR mentions in the texts of the PsyTAR corpus","authors":["A Sboev, G Rylkov, A Selivanov, I Moloshnikov… - AIP Conference …, 2023"],"snippet":"In this paper, for the first time, the accuracy of solving the problem of recognizing named entities of the ADR type for the PsyTAR corpus was evaluated. Initially, the corpus contained markup for solving the problems of detecting entities, classifying …","url":["https://pubs.aip.org/aip/acp/article/2849/1/400008/2909198"]}
{"year":"2023","title":"A Detailed Study on Preventing the Malicious URLs from Cyber Attacks","authors":["S Adnaan, G Tejasri, AVP Krishna, MGS Reddy - 2023 Third International …, 2023"],"snippet":"Today, there are more malicious URLs and cyber-attacks than ever. Cybercrimes are developing along with the software system’s progress. If we are able to stop one attack, then another one will follow in a different direction. These URLs were given …","url":["https://ieeexplore.ieee.org/abstract/document/10073865/"]}
{"year":"2023","title":"A Fast Method to Filter Noisy Parallel Data WMT2023 Shared Task on Parallel Data Curation","authors":["MC Nguyen-Hoang, VN Van, LM Nguyen"],"snippet":"The effectiveness of a machine translation (MT) system is intricately linked to the quality of its training dataset. In an era where websites offer an extensive repository of translations such as movie subtitles, stories, and TED Talks, the fundamental …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.37.pdf"]}
{"year":"2023","title":"A Few Words about ChatGPT","authors":["P Nag, S Mondal, A Sinha, S Mullick, R Mondal…"],"snippet":"ChatGPT is an artificial intelligence chatbot that uses natural language processing to generate human-like conversational talk. The language model can respond to inquiries and generate a wide range of written materials, including articles, social …","url":["https://www.researchgate.net/profile/Siddhartha-Chatterjee-3/publication/376488705_A_Few_Words_about_ChatGPT/links/657ac8a9fc4b416622c60f92/A-Few-Words-about-ChatGPT.pdf"]}
{"year":"2023","title":"A Formal Perspective on Byte-Pair Encoding","authors":["V Zouhar, C Meister, JL Gastaldi, L Du, T Vieira… - arXiv preprint arXiv …, 2023"],"snippet":"Byte-Pair Encoding (BPE) is a popular algorithm used for tokenizing data in NLP, despite being devised initially as a compression method. BPE appears to be a greedy algorithm at face value, but the underlying optimization problem that BPE …","url":["https://arxiv.org/pdf/2306.16837"]}
{"year":"2023","title":"A Framework for Responsible Development of Automated Student Feedback with Generative AI","authors":["ED Lindsay, A Johri, J Bjerva - arXiv preprint arXiv:2308.15334, 2023"],"snippet":"… roughly made up of 500 billion words of training data from Common Crawl, constituting a good chunk of the internet [7], rather than on a curated sample of similar assignments, with corresponding expert feedback. It is a generalized model …","url":["https://arxiv.org/pdf/2308.15334"]}
{"year":"2023","title":"A Golden Age: Conspiracy Theories' Relationship with Misinformation Outlets, News Media, and the Wider Internet","authors":["HWA Hanley, D Kumar, Z Durumeric - arXiv preprint arXiv:2301.10880, 2023"],"snippet":"… For each website in our dataset, we collect all the domain’s HTML pages that were indexed by Common Crawl before August 2021. In addition to Common Crawl data, we further utilize our own website scrapes. We utilize our own crawls, in …","url":["https://arxiv.org/pdf/2301.10880"]}
{"year":"2023","title":"A Graphical Approach to Document Layout Analysis","authors":["J Wang, M Krumdick, B Tong, H Halim, M Sokolov… - arXiv preprint arXiv …, 2023"],"snippet":"Document layout analysis (DLA) is the task of detecting the distinct, semantic content within a document and correctly classifying these items into an appropriate category (eg, text, title, figure). DLA pipelines enable users to convert documents into structured …","url":["https://arxiv.org/pdf/2308.02051"]}
{"year":"2023","title":"A Hierarchical Encoding-Decoding Scheme for Abstractive Multi-document Summarization","authors":["C Shen, L Cheng, Y You, L Bing - arXiv preprint arXiv:2305.08503, 2023"],"snippet":"Pre-trained language models (PLMs) have accomplished impressive achievements in abstractive single-document summarization (SDS). However, such benefits may not be readily extended to muti-document summarization (MDS), where the …","url":["https://arxiv.org/pdf/2305.08503"]}
{"year":"2023","title":"A Hybrid Extractive-Abstractive Framework with Pre & Post-Processing Techniques To Enhance Text Summarization","authors":["R Habu, R Ratnaparkhi, A Askhedkar, S Kulkarni - 2023 13th International …, 2023"],"snippet":"The goal of this paper is to enhance text summarization using a hybrid methodology. The process of producing a condensed version of a text while keeping its essential details is known as text summarization. In this study, we have presented a method …","url":["https://ieeexplore.ieee.org/abstract/document/10275584/"]}
{"year":"2023","title":"A Hybrid Method on Emotion Detection for Indonesian Tweets of COVID-19","authors":["D Purwitasari, ASS Ansyah, AP Kurniawan… - Jurnal RESTI (Rekayasa …, 2023"],"snippet":"As a result of the COVID-19 pandemic, there have been restrictions on activities outside the home which has caused people to interact more and express their emotions through social media platforms, one of which is Twitter. Previous studies …","url":["https://www.jurnal.iaii.or.id/index.php/RESTI/article/download/4816/735"]}
{"year":"2023","title":"A Hybrid Model for Multilingual OCR","authors":["D Etter, C Carpenter, N King - International Conference on Document Analysis and …, 2023"],"snippet":"… This large multilingual set is filtered from the Common Crawl corpus and is often used for the pretraining of large language models. The fonts to render the line images are selected from Google Fonts, Noto Fonts, and GNU Unifont. Table 1 …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41676-7_27"]}
{"year":"2023","title":"A Hybrid Transformer Ensemble Approach for Phishing Website Detection","authors":["KS Mandapati, S Meesala, D Maddela, K Ponnada… - … International Conference on …, 2023"],"snippet":"The internet has developed into a veritable informational gold mine in the era of the digital age, and URLs (Uniform Resource Locator) act as access points to enormous volumes of material. For a variety of applications, including web content classification …","url":["https://ieeexplore.ieee.org/abstract/document/10331880/"]}
{"year":"2023","title":"A Large Language Model Classification Framework (LLMCF)","authors":["K Khan"],"snippet":"The rapid advancement of Large Language Models (LLMs) has necessitated a comprehensive framework for categorizing and understanding their diverse characteristics. In response, this paper introduces the\" Large Language Model …","url":["http://ijmrap.com/wp-content/uploads/2023/09/IJMRAP-V6N4P38Y23.pdf"]}
{"year":"2023","title":"A LARGE-SCALE BENCHMARK TWITTER DATASETS FOR COVID-19 SENTIMENT ANALYSIS","authors":["P Rajaram, V Dhavamani"],"snippet":"… Similarly, for word embeddings, pretrained Word2Vec, GloVe, and fastText embeddings trained on Common Crawl and Wikipedia are used and have 300-D vectors. In addition, we used hybrid models, such as hybrid ranking (HyRank) and …","url":["https://www.irjmets.com/uploadedfiles/paper/issue_10_october_2023/45125/final/fin_irjmets1696734430.pdf"]}
{"year":"2023","title":"A Large-Scale Pretrained Deep Model for Phishing URL Detection","authors":["Y Wang, W Zhu, H Xu, Z Qin, K Ren, W Ma - ICASSP 2023-2023 IEEE International …, 2023"],"snippet":"Phishing attacks have always been a security issue that has attracted great attention in the cyber security community. Recently, the famous pre-trained models is being used as an anti-phishing solution. However, existing studies either simply transfer …","url":["https://ieeexplore.ieee.org/abstract/document/10095719/"]}
{"year":"2023","title":"A large-scale web accessibility analysis considering technology adoption","authors":["B Martins, C Duarte - Universal Access in the Information Society, 2023"],"snippet":"… To collect a sample fit for a large-scale accessibility evaluation, we obtained individual URLs from the CommonCrawl Footnote 6 set. We used the crawl data from November and December 2020. We removed possibly duplicated URLs, as …","url":["https://link.springer.com/article/10.1007/s10209-023-01010-0"]}
{"year":"2023","title":"A lightweight deep learning architecture for text embedding: Comparison between the usage of Transformers and Mixers for textual embedding","authors":["C Royer - 2023"],"snippet":"… These datasets contain all kinds of data, from Wikipedia which contains factual information to Common Crawl which is a collection of diverse websites. However, this demands considerable computing resources and long training times. To keep …","url":["https://www.diva-portal.org/smash/get/diva2:1799726/FULLTEXT01.pdf"]}
{"year":"2023","title":"A linear time approximation of Wasserstein distance with word embedding selection","authors":["S Otao, M Yamada - Proceedings of the 2023 Conference on Empirical …, 2023"],"snippet":"Wasserstein distance, which can be computed by solving the optimal transport problem, is a powerful method for measuring the dissimilarity between documents. In the NLP community, it is referred to as word mover’s distance (WMD). One of the …","url":["https://aclanthology.org/2023.emnlp-main.935.pdf"]}
{"year":"2023","title":"A low-resource approach to the grammatical error correction of Ukrainian","authors":["F Gomez, A Rozovskaya, D Roth - Proceedings of the Second Ukrainian Natural …, 2023"],"snippet":"We present our system that participated in the shared task on the grammatical error correction of Ukrainian. We have implemented two approaches that make use of large pre-trained language models and synthetic data, that have been used for error …","url":["https://aclanthology.org/2023.unlp-1.14.pdf"]}
{"year":"2023","title":"A Machine Learning Approach to Government Business Process Re-engineering","authors":["A Riyadi, M Kovacs, U Serdült, V Kryssanov - … Conference on Big Data and Smart …, 2023"],"snippet":"Governments around the world accumulate large amounts of data but rarely use them to make their daily work more effective. For example, data classification tasks are typically performed manually or with systems that utilize rules created by humans …","url":["https://ieeexplore.ieee.org/abstract/document/10066589/"]}
{"year":"2023","title":"A map of words: Retrieving the spatial layout of underground stations from natural","authors":["G Anceresi, D Gatti, T Vecchi, M Marelli, L Rinaldi"],"snippet":"Recent evidence has indicated that spatial representations, such as large-scale geographical maps, can be retrieved from natural language alone through cognitively plausible distributional-semantic models based on non-spatial …","url":["https://www.researchgate.net/profile/Giorgia-Anceresi/publication/370943870_A_map_of_words_Retrieving_the_spatial_layout_of_underground_stations_from_natural_language/links/646b6fc77b575d49292a039f/A-map-of-words-Retrieving-the-spatial-layout-of-underground-stations-from-natural-language.pdf"]}
{"year":"2023","title":"A meaningful learning method for zero-shot semantic segmentation","authors":["X Liu, S Bai, S An, S Wang, W Liu, X Zhao, Y Ma - Science China Information …, 2023"],"snippet":"Zero-shot semantic segmentation, which is developed to segment unseen categories, has attracted increasing attention due to its strong practicability. Previous approaches usually applied semantic-visual mapping based on seen categories to …","url":["https://link.springer.com/article/10.1007/s11432-022-3748-5"]}
{"year":"2023","title":"A Measurement-Based Quantum-Like Language Model for Text Matching","authors":["W Zhang, G Gan, H Gao, P Zhang, W Hui, Z Fan - … 22–26, 2022, Proceedings, Part III, 2023"],"snippet":"… The initialization method of word embeddings in the word representation utilizes the 300-dimensional GloVe word vectors pretrained from the 840B Common Crawl corpus [20]. Meanwhile, the word embeddings for the out-of-vocabulary words were …","url":["https://link.springer.com/chapter/10.1007/978-3-031-30111-7_4"]}
{"year":"2023","title":"A Multi-Modal Multilingual Benchmark for Document Image Classification","authors":["Y Fujinuma, S Varia, N Sankaran, S Appalaraju, B Min… - arXiv preprint arXiv …, 2023"],"snippet":"… LayoutXLM is also pretrained on documents from Common Crawl (CC) and Donut on synthetic Wikipedia documents (Syn. Wiki). InfoXLM … LayoutXLM is pretrained on PDFs from 53 languages extracted from Common Crawl6, thus …","url":["https://arxiv.org/pdf/2310.16356"]}
{"year":"2023","title":"A Multi-solution Study on GDPR AI-enabled Completeness Checking of DPAs","authors":["MI Azeem, S Abualhaija - arXiv preprint arXiv:2311.13881, 2023"],"snippet":"Specifying legal requirements for software systems to ensure their compliance with the applicable regulations is a major concern to requirements engineering (RE). Personal data which is collected by an organization is often shared with other …","url":["https://arxiv.org/pdf/2311.13881"]}
{"year":"2023","title":"A Multi-Task Multi-Stage Transitional Training Framework for Neural Chat Translation","authors":["C Zhou, Y Liang, F Meng, J Zhou, J Xu, H Wang… - IEEE Transactions on …, 2022"],"snippet":"Neural chat translation (NCT) aims to translate a cross-lingual chat between speakers of different languages. Existing context-aware NMT models cannot achieve satisfactory performances due to the following inherent problems: 1) limited …","url":["https://www.computer.org/csdl/journal/tp/5555/01/10003654/1JwLorw3TFK"]}
{"year":"2023","title":"A multimodal turn in Digital Humanities. Using contrastive machine learning models to explore, enrich, and analyze digital visual historical collections","authors":["T Smits, M Wevers - Digital Scholarship in the Humanities, 2023"],"snippet":"Until recently, most research in the Digital Humanities (DH) was monomodal, meaning that the object of analysis was either textual or visual. Seeking to integrate multimodality theory into the DH, this article demonstrates that recently developed …","url":["https://academic.oup.com/dsh/advance-article/doi/10.1093/llc/fqad008/7078540"]}
{"year":"2023","title":"A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","authors":["Y Bang, S Cahyawijaya, N Lee, W Dai, D Su, B Wilie… - arXiv preprint arXiv …, 2023"],"snippet":"… Based on the percentage of data in the CommonCrawl8, we group languages into 3 8CommonCrawl (http://commoncrawl.org) is the primary source of language pre-training data used in GPT3 … The languages are sorted based on the language …","url":["https://arxiv.org/pdf/2302.04023"]}
{"year":"2023","title":"A Neighbourhood-Aware Differential Privacy Mechanism for Static Word Embeddings","authors":["D Bollegala, S Otake, T Machide, K Kawarabayashi - arXiv preprint arXiv:2309.10551, 2023"],"snippet":"We propose a Neighbourhood-Aware Differential Privacy (NADP) mechanism considering the neighbourhood of a word in a pretrained static word embedding space to determine the minimal amount of noise required to guarantee a specified …","url":["https://arxiv.org/pdf/2309.10551"]}
{"year":"2023","title":"A New Era of Artificial Intelligence in Education: A Multifaceted Revolution","authors":["F Kamalov, I Gurrib - arXiv preprint arXiv:2305.18303, 2023"],"snippet":"The recent high performance of ChatGPT on several standardized academic test has thrust the topic of artificial intelligence (AI) into the mainstream conversation about the future of education. The objective of the present study is to investigate the …","url":["https://arxiv.org/pdf/2305.18303"]}
{"year":"2023","title":"A New Frontier: AI and Ancient Language Pedagogy","authors":["EAS Ross - Journal of Classics Teaching, 2023"],"snippet":"… OpenAI notes, and ChatGPT also reiterates when prompted, that the AI model was trained using a blend of filtered Common Crawl data, WebText, ebooks, and Wikipedia articles from before Q4 2021, so it is unable to answer questions or …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/A63EF69F5FE5529F0F45FB1EB655A9F7/S2058631023000430a.pdf/div-class-title-a-new-frontier-ai-and-ancient-language-pedagogy-div.pdf"]}
{"year":"2023","title":"A new phishing-website detection framework using ensemble classification and clustering","authors":["M Alsharaiah, A Abu-Shareha, M Abualhaj, L Baniata… - International Journal of Data …, 2023"],"snippet":"… The phishing samples were collected from the OpenPhish and Phish Tank, while the legitimate samples were gathered from different resources such as Common Crawl and Alexa. These samples were collected from January to May 2015 and May …","url":["http://growingscience.com/ijds/Vol7/ijdns_2023_8.pdf"]}
{"year":"2023","title":"A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews","authors":["CF Moreno-Garcia, C Jayne, E Elyan… - Decision Analytics Journal, 2023"],"snippet":"… examples of pre-trained transformer-based NLP systems are Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformers (GPT), which were trained with large language datasets, such as the …","url":["https://www.sciencedirect.com/science/article/pii/S2772662223000024"]}
{"year":"2023","title":"A novel Data and Model Centric artificial intelligence based approach in developing high-performance Named Entity Recognition for Bengali Language","authors":["KA Lima, K Md Hasib, S Azam, A Karim, S Montaha… - Plos one, 2023"],"snippet":"Named Entity Recognition (NER) plays a significant role in enhancing the performance of all types of domain specific applications in Natural Language Processing (NLP). According to the type of application, the goal of NER is to identify …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0287818"]}
{"year":"2023","title":"A PhD Student's Perspective on Research in NLP in the Era of Very Large Language Models","authors":["O Ignat, Z Jin, A Abzaliev, L Biester, S Castro, N Deng… - arXiv preprint arXiv …, 2023"],"snippet":"Recent progress in large language models has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse that ``it's all been solved.'' Not surprisingly, this has in turn made many …","url":["https://arxiv.org/pdf/2305.12544"]}
{"year":"2023","title":"A PHISHING DETECTION SYSTEM BASED ON INTELLIGENT DEEP LEARNING TECHNIQUES","authors":["GC Uzoaru, G Nwamuruamu, C Johnson-Okoronkwo - Int'l Journal of Education …, 2023"],"snippet":"… Approximately one million authentic and fraudulent URLs were employed in the dataset gathered from PhishTank and Common Crawl. Over 10,000 images and one million URLs were used in training for the CNN classifier and LSTM to create the …","url":["https://ijresd.org/index.php/IJRESD/article/download/61/42"]}
{"year":"2023","title":"A Predictive Factor Analysis of Social Biases and Task-Performance in Pretrained Masked Language Models","authors":["Y Zhou, J Camacho-Collados, D Bollegala - arXiv preprint arXiv:2310.12936, 2023"],"snippet":"… Domain: Full-text biomedical papers from the Semantic Scholar Open Research Corpus (S2ORC), PubMed Abstracts (PMed), PMC Fulltext articles and the Medical Information Mart for Intensive Care III (MIMIC3); Finally, we also consider a …","url":["https://arxiv.org/pdf/2310.12936"]}
{"year":"2023","title":"A Preference Judgment Interface for Authoritative Assessment","authors":["M Seifikar - 2023"],"snippet":"… of Common Crawl4. There is more information about document collection on the Track website. Each document in the collection that is provided for the 2https://huggingface.co/datasets/allenai/c4 3https://www.tensorflow.org/datasets/catalog/c4 4https://commoncrawl.org …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19151/Seifikar_Mahsa.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity","authors":["S Longpre, G Yauney, E Reif, K Lee, A Roberts, B Zoph… - arXiv preprint arXiv …, 2023"],"snippet":"… For each version we begin with Common Crawl data and remove all data that was scraped after the cutoff year. Following Luu et al. (2021), we measure the effect of temporal misalignment by using evaluation tasks (from News, Twitter, and …","url":["https://arxiv.org/pdf/2305.13169"]}
{"year":"2023","title":"A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis","authors":["I Gur, H Furuta, A Huang, M Safdari, Y Matsuo, D Eck… - arXiv preprint arXiv …, 2023"],"snippet":"… For HTML-denoising, we prepare the corpus from CommonCrawl with (Extracted) or without (Raw) subtree extraction around label elements on the documents. We also compare the initialization of base architectures before HTML-denoising; from …","url":["https://arxiv.org/pdf/2307.12856"]}
{"year":"2023","title":"A RelEntLess Benchmark for Modelling Graded Relations between Named Entities","authors":["A Ushio, JC Collados, S Schockaert - arXiv preprint arXiv:2305.15002, 2023"],"snippet":"Relations such as \"is influenced by\", \"is known for\" or \"is a competitor of\" are inherently graded: we can rank entity pairs based on how well they satisfy these relations, but it is hard to draw a line between those pairs that satisfy them and those …","url":["https://arxiv.org/pdf/2305.15002"]}
{"year":"2023","title":"A Research On The New Generation Artificial Intelligence Technology Generative Pretraining Transformer 3","authors":["N Aydın, OA Erdem - 2022 3rd International Informatics and Software …, 2022"],"snippet":"In the digitalizing world, Artificial Intelligence (AI) paves the way for the automation of routine work done by humans and makes life easier. Recently, there is no area where AI and its applications are not used in daily life, from health to education, from …","url":["https://ieeexplore.ieee.org/abstract/document/9998298/"]}
{"year":"2023","title":"A Review of Conversational Agents in Education","authors":["C Rodrigues, A Reis, R Pereira, P Martins, J Sousa… - International Conference on …, 2022"],"snippet":"The use of mobile conversations is increasing all around the world. A conversational agent (CA) is mostly useful due to the fast response times and their simple nature. Recently, we have seen the development and increasing use of dialog systems on …","url":["https://link.springer.com/chapter/10.1007/978-3-031-22918-3_37"]}
{"year":"2023","title":"A Review of Generative AI from Historical Perspectives","authors":["D Dasgupta, D Venugopal, KD Gupta"],"snippet":"Many applications of Generative AI (such as DALLE, GPT-3, ChatGPT, etc.) are making headline news in recent months and have been receiving both praise and criticism for their far reaching implications. Some of these applications include query …","url":["https://www.researchgate.net/profile/Kishor-Datta-Gupta/publication/368543465_A_Review_of_Generative_AI_from_Historical_Perspectives/links/63edde7f19130a1a4a82a316/A-Review-of-Generative-AI-from-Historical-Perspectives.pdf"]}
{"year":"2023","title":"A review of the approaches to neural machine translation","authors":["PK Buttar, MK Sachan - Natural Language Processing and Information …, 2023"],"snippet":"… (2019b) is a collection of 4.5 billion parallel sentences in 576 language pairs pulled from the snapshots of the CommonCrawl public dataset. WikiMatrix (Schwenk et al., 2019a) is another parallel collection of 135 million parallel sentences for 1,620 …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003244332-4/review-approaches-neural-machine-translation-preetpal-kaur-buttar-manoj-kumar-sachan"]}
{"year":"2023","title":"A review on big data based on deep neural network approaches","authors":["M Rithani, RP Kumar, S Doss - Artificial Intelligence Review, 2023"],"snippet":"… The highest recall and accuracy scores for Common Crawl (94.98 and 97.97, respectively) were linked with the highest F-measure score (96.46). There is no denying that this is an exciting piece of research, however the strategy used to …","url":["https://link.springer.com/article/10.1007/s10462-023-10512-5"]}
{"year":"2023","title":"A Review on Large Language Models: Architectures, Applications, Taxonomies, Open Issues and Challenges","authors":["MAK Raiaan, MSH Mukta, K Fatema, NM Fahad… - 2023"],"snippet":"… Besides, several corpus including the Common Crawl web corpus, the BooksCorpus dataset, and the English Wikipedia are also used … ) Books (Dec 2015) Books (Dec 2021) CommonCrawl (Sep 2019) CommonCrawl (Feb 2019) …","url":["https://www.techrxiv.org/articles/preprint/A_Review_on_Large_Language_Models_Architectures_Applications_Taxonomies_Open_Issues_and_Challenges/24171183/1/files/42414054.pdf"]}
{"year":"2023","title":"A Review on Malicious URLs Detection Using Machine Learning Methods","authors":["T Tabassum, MM Alam, MS Ejaz, MK Hasan - Journal of Engineering Research and …, 2023"],"snippet":"Malicious URLs are a serious threat to cybersecurity because they can compromise user security and inflict large financial losses. The extensiveness and adaptability of traditional detection approaches which rely on blacklists are limited when it comes to …","url":["http://archive.article4submit.com/id/eprint/2544/1/Alam25122023JERR110634.pdf"]}
{"year":"2023","title":"A Sentence Alignment Approach to Document Alignment and Multi-faceted Filtering for Curating Parallel Sentence Pairs from Web-crawled Data","authors":["S Steingrímsson"],"snippet":"This paper describes the AST submission to the WMT23 Shared Task on Parallel Data Curation. We experiment with two approaches for curating data from the provided web-scraped texts. We use sentence alignment to identify document …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.38.pdf"]}
{"year":"2023","title":"A Simple Baseline for Knowledge-Based Visual Question Answering","authors":["A Xenos, T Stafylakis, I Patras, G Tzimiropoulos - arXiv preprint arXiv:2310.13570, 2023"],"snippet":"This paper is on the problem of Knowledge-Based Visual Question Answering (KB-VQA). Recent works have emphasized the significance of incorporating both explicit (through external databases) and implicit (through LLMs) knowledge to answer questions …","url":["https://arxiv.org/pdf/2310.13570"]}
{"year":"2023","title":"A Study of Continual Learning Under Language Shift","authors":["E Gogoulou, T Lesort, M Boman, J Nivre - arXiv preprint arXiv:2311.01200, 2023"],"snippet":"The recent increase in data and model scale for language model pre-training has led to huge training costs. In scenarios where new data become available over time, updating a model instead of fully retraining it would therefore provide significant …","url":["https://arxiv.org/pdf/2311.01200"]}
{"year":"2023","title":"A Study of Multilingual versus Meta-Learning for Language Model Pre-Training for Adaptation to Unseen Low Resource Languages","authors":["J Khatri, R Murthy, AP Azad, P Bhattacharyya"],"snippet":"In this paper, we compare two approaches to train a multilingual language model:(i) simple multilingual learning using data-mixing, and (ii) meta-learning. We examine the performance of these models by extending them to unseen language pairs and …","url":["https://www.cse.iitb.ac.in/~pb/papers/mts23-maml.pdf"]}
{"year":"2023","title":"A Study on Bias Detection and Classification in Natural Language Processing","authors":["AS Evans, M Helena, C Luisa - 2023"],"snippet":"… An example of this is the work done by Luccioni and Viviano [19] on the Common Crawl Corpus1, with a focus on finding instances of Hate Speech and sexually explicit content. The Common Crawl is a multilingual corpus, composed of 200 to …","url":["https://www.researchsquare.com/article/rs-3351695/latest.pdf"]}
{"year":"2023","title":"A Study on the Utilization of OpenAI ChatGPT as a Second Language Learning Tool","authors":["S Kim, J Shim, J Shim - Journal of Multimedia Information System, 2023"],"snippet":"In November 2022, ChatGPT was introduced and caused a sensation, gathering 100 million users only within two months. ChatGPT’s capability of generating high-quality sentences demonstrated potential to be applied in a wide range of fields. In this …","url":["http://www.jmis.org/archive/view_article?pid=jmis-10-1-79"]}
{"year":"2023","title":"A Survey of Large Language Models in Medicine: Progress, Application, and Challenge","authors":["H Zhou, B Gu, X Zou, Y Li, SS Chen, P Zhou, J Liu… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs), such as ChatGPT, have achieved substantial attention due to their impressive human language understanding and generation capabilities. Therefore, the application of LLMs in medicine to assist physicians and …","url":["https://arxiv.org/pdf/2311.05112"]}
{"year":"2023","title":"A Survey of Large Language Models","authors":["WX Zhao, K Zhou, J Li, T Tang, X Wang, Y Hou, Y Min… - arXiv preprint arXiv …, 2023"],"snippet":"… Based on CommonCrawl, there are four filtered datasets that are commonly used in existing work: C4 [71], CCStories [102], CC-News [27], and RealNews [103]. The Colossal Clean Crawled Corpus (C4) includes five variants10, namely en (806G), en.noclean …","url":["https://arxiv.org/pdf/2303.18223"]}
{"year":"2023","title":"A Survey of Text Representation and Embedding Techniques in NLP","authors":["R Patil, S Boit, V Gudivada, J Nandigam - IEEE Access, 2023"],"snippet":"Natural Language Processing (NLP) is a research field where a language in consideration is processed to understand its syntactic, semantic, and sentimental aspects. The advancement in the NLP area has helped solve problems in the …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10098736.pdf"]}
{"year":"2023","title":"A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends","authors":["X Qu, Y Gu, Q Xia, Z Li, Z Wang, B Huai - arXiv preprint arXiv:2302.03512, 2023"],"snippet":"As more and more Arabic texts emerged on the Internet, extracting important information from these Arabic texts is especially useful. As a fundamental technology, Named entity recognition (NER) serves as the core component in information …","url":["https://arxiv.org/pdf/2302.03512"]}
{"year":"2023","title":"A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware","authors":["S Zhang, A Sohrabizadeh, C Wan, Z Huang, Z Hu… - arXiv preprint arXiv …, 2023"],"snippet":"… -dimensional vectors concatenating the average embedding of the post title and that of all the post’s comments, the post’s score, and the number of comments made on the post, where the average embedding is obtained by averaging the 300-dimensional …","url":["https://arxiv.org/pdf/2306.14052"]}
{"year":"2023","title":"A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage","authors":["MU Hadi, R Qureshi, A Shah, M Irfan, A Zafar… - 2023"],"snippet":"Within the vast expanse of computerized language processing, a revolutionary entity known as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to comprehend intricate linguistic patterns and conjure coherent and …","url":["https://www.techrxiv.org/articles/preprint/A_Survey_on_Large_Language_Models_Applications_Challenges_Limitations_and_Practical_Usage/23589741/1/files/41501037.pdf"]}
{"year":"2023","title":"A Survey on LLM-gernerated Text Detection: Necessity, Methods, and Future Directions","authors":["J Wu, S Yang, R Zhan, Y Yuan, DF Wong, LS Chao - arXiv preprint arXiv:2310.14724, 2023"],"snippet":"The powerful ability to understand, follow, and generate complex language emerging from large language models (LLMs) makes LLM-generated text flood many areas of our daily lives at an incredible speed and is widely accepted by …","url":["https://arxiv.org/pdf/2310.14724"]}
{"year":"2023","title":"A Systematic Literature Review on Phishing Website Detection Techniques","authors":["A Safi, S Singh - Journal of King Saud University-Computer and …, 2023"],"snippet":"Phishing is a fraud attempt in which an attacker acts as a trusted person or entity to obtain sensitive information from an internet user. In this Systematic Literature Survey (SLR), different phishing detection approaches, namely Lists Based, Visual …","url":["https://www.sciencedirect.com/science/article/pii/S1319157823000034"]}
{"year":"2023","title":"A systematic review of applications of natural language processing and future challenges with special emphasis in text-based emotion detection","authors":["S Kusal, S Patil, J Choudrie, K Kotecha, D Vora… - Artificial Intelligence Review, 2023"],"snippet":"Artificial Intelligence (AI) has been used for processing data to make decisions, Interact with humans, and understand their feelings and emotions. With the advent of the Internet, people share and express their thoughts on day-to-day activities and …","url":["https://link.springer.com/article/10.1007/s10462-023-10509-0"]}
{"year":"2023","title":"A Systematic Review of Transformer-Based Pre-Trained Language Models through Self-Supervised Learning","authors":["E Kotei, R Thirunavukarasu - Information, 2023"],"snippet":"… A typical example is the CommonCrawl corpus [75]. Models such as IndoNLG [76], MuRIL [77], IndicNLPSuite [78], mT5 [79], mT6 [80], XLM… derived from Common Crawl corpus [75] Introduced the mT5 multilingual variant of the T5 model pretrained …","url":["https://www.mdpi.com/2078-2489/14/3/187"]}
{"year":"2023","title":"A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets","authors":["MTR Laskar, MS Bari, M Rahman, MAH Bhuiyan… - arXiv preprint arXiv …, 2023"],"snippet":"The development of large language models (LLMs) such as ChatGPT has brought a lot of attention recently. However, their evaluation in the benchmark academic datasets remains under-explored due to the difficulty of evaluating the generative …","url":["https://arxiv.org/pdf/2305.18486"]}
{"year":"2023","title":"A T5-based interpretable reading comprehension model with more accurate evidence training","authors":["B Guan, X Zhu, S Yuan - Information Processing & Management, 2024"],"snippet":"Pre-trained language models (PLMs) have achieved outstanding performance on Machine Reading Comprehension (MRC) tasks, but these models’ interpretability remains uncertain. In this paper, we exploit the strengths of the pre-trained T5 (Text-to-Text …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323003217"]}
{"year":"2023","title":"A Thorough Analysis of E-commerce Customer Reviews in Arabic Language Using Deep Learning Techniques for Successful Marketing Decisions","authors":["N Hicham, H Nassera, S Karim"],"snippet":"… AraVec provides six-word embedding models that have already been pretrained, and these models use data from Twitter, Wikipedia, and Common Crawl. The overall quantity of tokens that were utilized in the creation of the models is more remarkable …","url":["https://www.iaeng.org/IJAM/issues_v53/issue_4/IJAM_53_4_42.pdf"]}
{"year":"2023","title":"A Tool Kit for Relation Induction in Text Analysis","authors":["DS Stoltz, MA Taylor, JSK Dudley - 2023"],"snippet":"Distances derived from word embeddings can measure a range of gradational relations—similarity, hierarchy, entailment, and stereotype—and can be used at the document-and author-level in ways that overcome some of the limitations of …","url":["https://osf.io/preprints/socarxiv/9bwzr/download"]}
{"year":"2023","title":"A transformer-based deep learning model for Persian moral sentiment analysis","authors":["B Karami, F Bakouie, S Gharibzadeh - Journal of Information Science, 2023"],"snippet":"Moral expressions in online communications can have a serious impact on framing discussions and subsequent online behaviours. Despite research on extracting moral sentiment from English text, other low-resource languages, such as Persian …","url":["https://journals.sagepub.com/doi/abs/10.1177/01655515231188344"]}
{"year":"2023","title":"A Transformer-based Generative Adversarial Learning to Detect Sarcasm from Bengali Text with Correct Classification of Confusing Text","authors":["SK Lora, I Jahan, R Hussain, R Shahriyar… - Heliyon"],"snippet":"Sarcasm detection research in Bengali is still limited due to a lack of relevant resources. In this context, getting high-quality annotated data is costly and time-consuming. Therefore, in this paper, we present a transformer-based generative adversarial …","url":["https://www.cell.com/heliyon/pdf/S2405-8440(23)09739-6.pdf"]}
{"year":"2023","title":"A transformer-based multi-task framework for joint detection of aggression and hate on social media data","authors":["S Ghosh, A Priyankar, A Ekbal, P Bhattacharyya - Natural Language Engineering, 2023"],"snippet":"… It is a massive multi-lingual model that was trained on 2.5 TB of CommonCrawl data in 100 distinct languages. It outperforms other transformer models, such as Bidirectional Encoder Representations from Transformers (BERT) and Multi-lingual …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C551F3E0504E5595762037691EE27271/S1351324923000104a.pdf/div-class-title-a-transformer-based-multi-task-framework-for-joint-detection-of-aggression-and-hate-on-social-media-data-div.pdf"]}
{"year":"2023","title":"A User-Centered Evaluation of Spanish Text Simplification","authors":["A de Wynter, A Hevia, SQ Chen - arXiv preprint arXiv:2308.07556, 2023"],"snippet":"We present an evaluation of text simplification (TS) in Spanish for a production system, by means of two corpora focused in both complex-sentence and complex-word identification. We compare the most prevalent Spanish-specific readability scores …","url":["https://arxiv.org/pdf/2308.07556"]}
{"year":"2023","title":"A Vision for Semantically Enriched Data Science","authors":["U Khurana, K Srinivas, S Galhotra, H Samulowitz - arXiv preprint arXiv:2303.01378, 2023"],"snippet":"The recent efforts in automation of machine learning or data science has achieved success in various tasks such as hyper-parameter optimization or model selection. However, key areas such as utilizing domain knowledge and data semantics are …","url":["https://arxiv.org/pdf/2303.01378"]}
{"year":"2023","title":"ABCD Team at FinancES 2023: An Unified Generative Framework for the Financial Targeted Sentiment Analysis in Spanish","authors":["NLT Nguyen - 2023"],"snippet":"This paper presents our participation in the IBERLEF 2023 Task-FinancES in Spanish, focusing on two sub-tasks: Financial targeted sentiment analysis and Financial Sentiment Analysis at the document level for companies and consumers …","url":["https://ceur-ws.org/Vol-3496/finances-paper2.pdf"]}
{"year":"2023","title":"Abstractive summarization with deep reinforcement learning using semantic similarity rewards","authors":["FB Fikri, K Oflazer, B Yanıkoğlu - Natural Language Engineering, 2023"],"snippet":"Abstractive summarization is an approach to document summarization that is not limited to selecting sentences from the document but can generate new sentences as well. We address the two main challenges in abstractive summarization: how to …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/740B4B5903AE80FE14709F5DAEE7AD41/S1351324923000505a.pdf/abstractive_summarization_with_deep_reinforcement_learning_using_semantic_similarity_rewards.pdf"]}
{"year":"2023","title":"Abstractive Text Summarization based on Transformer Deep Neural Networks","authors":["V Davidović - 2023"],"snippet":"… GPT-3 (Generative Pre-trained Transformers) [32] is large autoregressive language model (LLM) with 175 billion of parameters that is trained on 300 billion tokens of text (570GB in total Common Crawl dataset) and tested in the fewshot …","url":["https://www.inf.uniri.hr/images/studiji/poslijediplomski/kvalifikacijski/Davidovic_Vlatka_Kvalifikacijski_rad.pdf"]}
{"year":"2023","title":"ABSTRACTIVE TEXT SUMMARIZATION FOR MORPHOLOGICALLY RICH LANGUAGES","authors":["B Baykara - 2023"],"snippet":"The exponential growth in the number of documents available on the Web has turned finding the relevant piece of information into a challenging, tedious, and timeconsuming activity. Accordingly, automatic text summarization has become an …","url":["https://www.cmpe.boun.edu.tr/~gungort/theses/Abstractive%20Text%20Summarization%20for%20Morphologically%20Rich%20Languages.pdf"]}
{"year":"2023","title":"Abstractive Text Summarization for Tamil Language Using m-T5","authors":["C Saraswathi, V Prinitha, J Briskilal - Inventive Systems and Control: Proceedings of …, 2023"],"snippet":"Summarization is the act of reducing a long form of text to a shorter version by lowering the length of the original text while retaining and keeping the summary’s core and the informational parts which conveys the content’s meaning. Summarizing …","url":["https://link.springer.com/chapter/10.1007/978-981-99-1624-5_35"]}
{"year":"2023","title":"Abstractive Text Summarization of Hindi Corpus Using Transformer Encoder-Decoder Model","authors":["R Bhansali, A Bhave, G Bharat, V Mahajan, ML Dhore - International Symposium on …, 2023"],"snippet":"… FastText has been trained on Hindi text procured from Wikipedia and Common Crawl using positional weights with a Continuous Bag-of-Words (CBOW) model giving word representations of dimension 300. This model is known to give efficient …","url":["https://link.springer.com/chapter/10.1007/978-981-19-8094-7_13"]}
{"year":"2023","title":"Abusive Span Detection for Vietnamese Narrative Texts","authors":["NT Nguyen, K Thi-Kim Phan, DV Nguyen… - Proceedings of the 12th …, 2023"],"snippet":"Abuse in its various forms, including physical, psychological, verbal, sexual, financial, and cultural, has a negative impact on mental health. However, there are limited studies on applying natural language processing (NLP) in this field in Vietnam …","url":["https://dl.acm.org/doi/abs/10.1145/3628797.3628921"]}
{"year":"2023","title":"AcademicGPT: Empowering Academic Research","authors":["S Wei, X Xu, X Qi, X Yin, J Xia, J Ren, P Tang, Y Zhong… - arXiv preprint arXiv …, 2023"],"snippet":"… for classification using the obtained 200K data; (4) we conduct classification on the common crawl data and clean out 12.7B tokens from CC. … Please assess the provided CommonCrawl sample based on the following criteria and return the …","url":["https://arxiv.org/pdf/2311.12315"]}
{"year":"2023","title":"Accelerating the integration of ChatGPT and other large‐scale AI models into biomedical research and healthcare","authors":["DQ Wang, LY Feng, JG Ye, JG Zou, YF Zheng - MedComm–Future Medicine, 2023"],"snippet":"… For example, GPT-3 was trained on 300B tokens, with 60% coming from the filtered Common Crawl data set, and the rest from webtext2 (used to train GPT-2), Books1, Books2, Wikipedia, and code datasets (such as GitHub Code). The …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1002/mef2.43"]}
{"year":"2023","title":"Accessing Higher Dimensions for Unsupervised Word Translation","authors":["SI Wang - arXiv preprint arXiv:2305.14200, 2023"],"snippet":"The striking ability of unsupervised word translation has been demonstrated with the help of word vectors / pretraining; however, they require large amounts of data and usually fails if the data come from different domains. We propose coocmap, a …","url":["https://arxiv.org/pdf/2305.14200"]}
{"year":"2023","title":"Accurate and Reliable Classification of Unstructured Reports on Their Diagnostic Goal Using BERT Models","authors":["MT Rietberg, VB Nguyen, J Geerdink, O Vijlbrief… - Diagnostics, 2023"],"snippet":"Understanding the diagnostic goal of medical reports is valuable information for understanding patient flows. This work focuses on extracting the reason for taking an MRI scan of Multiple Sclerosis (MS) patients using the attached free-form reports …","url":["https://www.mdpi.com/2075-4418/13/7/1251"]}
{"year":"2023","title":"Accurate Knowledge Distillation with n-best Reranking","authors":["H Setiawan - arXiv preprint arXiv:2305.12057, 2023"],"snippet":"We propose extending the Sequence-level Knowledge Distillation (Kim and Rush, 2016) with n-best reranking to consider not only the top-1 hypotheses but also the top n-best hypotheses of teacher models. Our approach leverages a diverse set of …","url":["https://arxiv.org/pdf/2305.12057"]}
{"year":"2023","title":"Acoustic and linguistic representations for speech continuous emotion recognition in call center conversations","authors":["M Macary, M Tahon, Y Estève, D Luzzati - arXiv preprint arXiv:2310.04481, 2023"],"snippet":"The goal of our research is to automatically retrieve the satisfaction and the frustration in real-life call-center conversations. This study focuses an industrial application in which the customer satisfaction is continuously tracked down to …","url":["https://arxiv.org/pdf/2310.04481"]}
{"year":"2023","title":"ADA: An Attention-Based Data Augmentation Approach to Handle Imbalanced Textual Datasets","authors":["AK Sah, M Abulaish - … : 29th International Conference, ICONIP 2022, Virtual …, 2023"],"snippet":"… For classification tasks throughout this work, we have used \\(300-\\)dimensional GloVe embeddings trained on the Common Crawl dataset with 840B tokens. For BERT-related tasks, we have used the BERT base uncased pre-trained model …","url":["https://link.springer.com/chapter/10.1007/978-981-99-1639-9_40"]}
{"year":"2023","title":"Adaptation of Enterprise Modeling Methods for Large Language Models","authors":["BS Barn, S Barat, K Sandkuhl - IFIP Working Conference on The Practice of …, 2023"],"snippet":"… GPT-3 uses 175 billion parameters and is trained on data from the Common Crawl data set Footnote 1 comprising nearly a trillion words. The development in large language models and their evolution has been widely documented and the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-48583-1_1"]}
{"year":"2023","title":"Adapting an English Corpus and a Question Answering System for Slovene","authors":["U Šmajdek, M Zupanič, M Zirkelbach, M Jazbinšek - Slovenščina 2.0: empirične …, 2023"],"snippet":"Pomanjkanje ustreznih podatkov za učenje je ena od ključnih težav pri razvoju slovenskih modelov za odgovarjanje na vprašanja (QA). Sodobna orodja za strojno prevajanje lahko to težavo rešijo, vendar pa se pri njihovi uporabi soočimo z novih …","url":["https://journals.uni-lj.si/slovenscina2/article/download/12064/13780"]}
{"year":"2023","title":"Adapting Grounded Visual Question Answering Models to Low Resource Languages","authors":["Y Wang, J Pfeiffer, N Carion, Y LeCun, A Kamath - … of the IEEE/CVF Conference on …, 2023"],"snippet":"… by classifying and filtering the Common Crawl dataset by languages. The statistics for different languages in OSCAR are shown in Table 1. Compared to unimodal datasets, multilingual multimodal datasets are much harder to obtain and …","url":["https://openaccess.thecvf.com/content/CVPR2023W/MULA/papers/Wang_Adapting_Grounded_Visual_Question_Answering_Models_to_Low_Resource_Languages_CVPRW_2023_paper.pdf"]}
{"year":"2023","title":"Adaptive Training Distributions with Scalable Online Bilevel Optimization","authors":["D Grangier, P Ablin, A Hannun - arXiv preprint arXiv:2311.11973, 2023"],"snippet":"Large neural networks pretrained on web-scale corpora are central to modern machine learning. In this paradigm, the distribution of the large, heterogeneous pretraining data rarely matches that of the application domain. This work considers …","url":["https://arxiv.org/pdf/2311.11973"]}
{"year":"2023","title":"Adding guardrails to advanced chatbots","authors":["Y Wang, L Singh - arXiv preprint arXiv:2306.07500, 2023"],"snippet":"… According to OpenAI, 60% of the training data come from Common Crawl, a large data set consisting of web pages, extracted metadata and text extractions through a big web crawler since 2008. Another 22% of data are from WebText2, containing all …","url":["https://arxiv.org/pdf/2306.07500"]}
{"year":"2023","title":"Adding Instructions during Pretraining: Effective Way of Controlling Toxicity in Language Models","authors":["S Prabhumoye, M Patwary, M Shoeybi, B Catanzaro - arXiv preprint arXiv …, 2023"],"snippet":"Pretrained large language models have become indispensable for solving various natural language processing (NLP) tasks. However, safely deploying them in real world applications is challenging because they generate toxic content. To address …","url":["https://arxiv.org/pdf/2302.07388"]}
{"year":"2023","title":"Addressing Controversial Topics in Search Engines","authors":["Y Ajjour - 2023"],"snippet":"… top 500 documents from the Common Crawl Index1 on eight controversial topics. Then, several sequence-to-sequence classifiers were developed to perform the task both in a cross-topic and in-topic settings. The results of the experiments show very …","url":["https://e-pub.uni-weimar.de/opus4/files/6403/diss-ajjour-frame.pdf"]}
{"year":"2023","title":"ADM+ S submission to the Safe and responsible AI in Australia discussion paper","authors":["K Weatherall - 2023"],"snippet":"The ADM+ S is pleased to have this opportunity to engage with an important and complex question which confronts Australia: how should the Australian federal government take actionregulatory or otherwise-to promote artificial intelligence (and …","url":["https://apo.org.au/node/323896"]}
{"year":"2023","title":"Adopting machine translation in the healthcare sector: A methodological multi-criteria review","authors":["M Zappatore, G Ruggieri - Computer Speech & Language, 2023"],"snippet":"Background: The recent advances in machine translation (MT) offer an appealing and low-cost solution to overcome language barriers in multiple contexts (eg, travelling, cultural interaction, digital content localisation). However, highly-technical …","url":["https://www.sciencedirect.com/science/article/pii/S0885230823001018"]}
{"year":"2023","title":"Advanced Methods to Audit Online Web Services","authors":["P Vallina - 2023"],"snippet":"Online web services have grown dramatically in size and diversity in the last years, becoming essential components of our daily life and allowing us to conduct elementary tasks like working, getting informed, or keeping in contact with relatives …","url":["https://dspace.networks.imdea.org/bitstream/handle/20.500.12761/1668/Pelayo_Vallina_Thesis.pdf?sequence=1"]}
{"year":"2023","title":"Advanced Network Technologies and Intelligent Computing: Second International Conference, ANTIC 2022, Varanasi, India, December 22–24, 2022, Proceedings …","authors":["I Woungang, SK Dhurandher, KK Pattanaik, A Verma… - 2023"],"snippet":"The 2nd International Conference on Advanced Network Technologies and Intelligent Computing (ANTIC-2022) was organized by Department of Computer Science, Institute of Science, Banaras Hindu University, Varanasi, India in hybrid …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=uhm1EAAAQBAJ&oi=fnd&pg=PR6&dq=commoncrawl&ots=Cw825CR0q7&sig=4GzV7hu-Io1Be66sWi1KTmgmssc"]}
{"year":"2023","title":"Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers","authors":["S Bengesi, H El-Sayed, MK Sarker, Y Houkpati… - arXiv preprint arXiv …, 2023"],"snippet":"… CommonCrawl was used to train the model, which was tested on all domains of NLP, and it had promising few-short and zero-shot performance. This version was further improved to GPT 3.5, which was used to develop ChatGPT. Considerable …","url":["https://arxiv.org/pdf/2311.10242"]}
{"year":"2023","title":"Advances in apparent conceptual physics reasoning in ChatGPT-4","authors":["CG West - arXiv preprint arXiv:2303.17012, 2023"],"snippet":"… While the exact details of the text which was used to “train” ChatGPT are a proprietary secret, it is known that its reading material was largely drawn from the “Common Crawl” corpus [18], an open repository of data scraped from text found on the public …","url":["https://arxiv.org/pdf/2303.17012"]}
{"year":"2023","title":"Advances in monolingual and crosslingual automatic disability annotation in Spanish","authors":["I Goenaga Azcarate, E Andrés Santamaría… - 2023"],"snippet":"Background Unlike diseases, automatic recognition of disabilities has not received the same attention in the area of medical NLP. Progress in this direction is hampered by obstacles like the lack of annotated corpus. Neural architectures learn …","url":["https://addi.ehu.es/bitstream/handle/10810/63451/s12859-023-05372-3.pdf?sequence=1"]}
{"year":"2023","title":"Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT","authors":["M Hu, S Pan, Y Li, X Yang - arXiv preprint arXiv:2304.04920, 2023"],"snippet":"In this paper, we aimed to provide a review and tutorial for researchers in the field of medical imaging using language models to improve their tasks at hand. We began by providing an overview of the history and concepts of language models, with a …","url":["https://arxiv.org/pdf/2304.04920"]}
{"year":"2023","title":"Advancing Neural Encoding of Portuguese with Transformer Albertina PT","authors":["J Rodrigues, L Gomes, J Silva, A Branco, R Santos… - arXiv preprint arXiv …, 2023"],"snippet":"To advance the neural encoding of Portuguese (PT), and a fortiori the technological preparation of this language for the digital age, we developed a Transformer-based foundation model that sets a new state of the art in this respect for two of its variants …","url":["https://arxiv.org/pdf/2305.06721"]}
{"year":"2023","title":"Adversarial Capsule Networks for Romanian Satire Detection and Sentiment Analysis","authors":["SV Echim, RA Smădu, AM Avram, DC Cercel, F Pop - International Conference on …, 2023"],"snippet":"Satire detection and sentiment analysis are intensively explored natural language processing (NLP) tasks that study the identification of the satirical tone from texts and extracting sentiments in relationship with their targets. In languages with fewer …","url":["https://arxiv.org/pdf/2306.07845"]}
{"year":"2023","title":"AfriCLIRMatrix: Enabling Cross-Lingual Information Retrieval for African Languages","authors":["O Ogundepo, X Zhang, S Sun, K Duh, J Lin - Proceedings of the 2022 Conference on …, 2022"],"snippet":"… is to exploit existing large multilingual corpora, eg, the Common Crawl1 and Wikipedia. For example, the HC4 corpus for cross-lingual information retrieval was created from Common Crawl data (Lawrie et al.… 1https://commoncrawl.org 2https://www.elastic.co/elasticsearch/ …","url":["https://aclanthology.org/2022.emnlp-main.597.pdf"]}
{"year":"2023","title":"Aggregating Users' Online Opinions Attributes and News Influence for Cryptocurrencies Reputation Generation","authors":["A Boumhidi, A Benlahbib - Journal of Universal Computer Science, 2023"],"snippet":"… The model was pre-trained on the Common Crawl’s web crawl corpus (C4) and it achieved state-of-the-art results on many natural language processing tasks while being flexible enough to be fine-tuned to a variety of important downstream tasks …","url":["https://search.proquest.com/openview/7239ef0ee44e31cc2e498915e4b2d0fc/1?pq-origsite=gscholar&cbl=6474026"]}
{"year":"2023","title":"Agile Modeling: From Concept to Classifier in Minutes","authors":["O Stretcu, E Vendrow, K Hata, K Viswanathan, V Ferrari… - Proceedings of the IEEE …, 2023"],"snippet":"… Since our prototype requires an unlabeled source of images from which to source training labels, we use the LAION-400M dataset [53], due to its large size and comprehensive construction based on the large Common Crawl web corpus. We …","url":["https://openaccess.thecvf.com/content/ICCV2023/papers/Stretcu_Agile_Modeling_From_Concept_to_Classifier_in_Minutes_ICCV_2023_paper.pdf"]}
{"year":"2023","title":"Agile Modeling: Image Classification with Domain Experts in the Loop","authors":["O Stretcu, E Vendrow, K Hata, K Viswanathan, V Ferrari… - arXiv preprint arXiv …, 2023"],"snippet":"Machine learning is not readily accessible to domain experts from many fields, blocked by issues ranging from data mining to model training. We argue that domain experts should be at the center of the modeling process, and we introduce the \"Agile …","url":["https://arxiv.org/pdf/2302.12948"]}
{"year":"2023","title":"AGNETHA FLORE AND RÜDIGER LANG","authors":["APMKIN LARGE, H NUHN, A OSWALD - … Future of Project Management: Adapting to …, 2023"],"snippet":"Digital Transformation seems to be ubiquitous, and it is radically changing humans’ lives. Artificial Intelligence (AI) and Machine Learning (ML) are two very effective drivers of this transformation. Following Vial (2019), we understand Digital …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=tFTlEAAAQBAJ&oi=fnd&pg=PA40&dq=commoncrawl&ots=2iCcz5tepo&sig=Y81TEcpnEW8sxQC82hsdvF_XKzM"]}
{"year":"2023","title":"AI and Law: The Next Generation","authors":["K Lee, AF Cooper, J Grimmelman, D Ippolito - 2023"],"snippet":"It’s impossible to read about technological innovation right now without hearing the term “generative AI.” We are in a moment of seemingly nonstop excitement (and seemingly nonstop lawsuits) about the future of AI-assisted content creation, and the …","url":["https://www.researchgate.net/profile/A-Cooper-2/publication/372251056_AI_and_Law_The_Next_Generation_An_explainer_series/links/64ad12b7b9ed6874a51152ec/AI-and-Law-The-Next-Generation-An-explainer-series.pdf"]}
{"year":"2023","title":"AI and the Creative Process: Part Two","authors":["J Hutson - JSTOR Daily, 2023"],"snippet":"… Stable Difusion by Stability AI, for example, was developed using image and caption pairs from the LAION-5B dataset, a publicly accessible collection derived from Common Crawl data gathered from the web. This vas dataset consiss of 5 …","url":["https://digitalcommons.lindenwood.edu/cgi/viewcontent.cgi?article=1514&context=faculty-research-papers"]}
{"year":"2023","title":"AI and the FCI: Can ChatGPT Project an Understanding of Introductory Physics?","authors":["CG West - arXiv preprint arXiv:2303.01067, 2023"],"snippet":"… While the exact details of the text which was used to “train” ChatGPT are a proprietary secret, it is known that its reading material was largely drawn from the “Common Crawl” corpus [13], an open repository of data scraped from text found on the public …","url":["https://arxiv.org/pdf/2303.01067"]}
{"year":"2023","title":"AI as a License Review Assistant","authors":["N Gustafson-Sundell - 2023"],"snippet":"I will present the steps we have taken to develop a prototype AI assistant for license review. I’ll explain our criteria for the selection of an AI tool for this project. We reviewed ChatGPT, Claude 2, Bard, and PDF readers. My goal was to develop an …","url":["https://cornerstone.lib.mnsu.edu/cgi/viewcontent.cgi?article=1209&context=lib_services_fac_pubs"]}
{"year":"2023","title":"AI Design Issues in Education","authors":["J Adams, KL Riddle - ITP Research Symposium 2022 30 November–2 …"],"snippet":"… CommonCOW: Massively huge web corpora from CommonCrawl data and a method to distribute them freely under restrictive EU copyright laws. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)(pp …","url":["http://www.unitec.ac.nz/epress/wp-content/uploads/2023/11/ITP2022-Proceedings.pdf#page=119"]}
{"year":"2023","title":"AI Ethics and Critique for Robotics","authors":["W Agnew - 2023"],"snippet":"In this thesis I consider using 3D computer vision for social good. In particular, I present a broad and deep array of AI ethics methodologies and practices necessary to assess the harms and benefits of a particular AI technology or application. Many …","url":["https://search.proquest.com/openview/d83ea4d6762d3472dfa408c410e6d5a3/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"AI for social good: social media mining of migration discourse","authors":["A Khatua - 2023"],"snippet":"The number of international migrants has steadily increased over the years, and it has become one of the pressing issues in today’s globalized world. Our bibliometric review of around 400 articles on Scopus platform indicates an increased interest in …","url":["https://www.repo.uni-hannover.de/bitstream/handle/123456789/15018/Thesis_10%20Oct%202023.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"AI model GPT-3 (dis) informs us better than humans","authors":["G Spitale, N Biller-Andorno, F Germani - arXiv preprint arXiv:2301.11924, 2023"],"snippet":"Artificial intelligence is changing the way we create and evaluate information, and this is happening during an infodemic, which has been having dramatic effects on global health. In this paper we evaluate whether recruited individuals can …","url":["https://arxiv.org/pdf/2301.11924"]}
{"year":"2023","title":"AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap","authors":["QV Liao, JW Vaughan - arXiv preprint arXiv:2306.01941, 2023"],"snippet":"The rise of powerful large language models (LLMs) brings about tremendous opportunities for innovation but also looming risks for individuals and society at large. We have reached a pivotal moment for ensuring that LLMs and LLM-infused …","url":["https://arxiv.org/pdf/2306.01941"]}
{"year":"2023","title":"AI, Large Language Models and University Education","authors":["D Psarras, Z Sotireli, I Valsamara, I Pitas"],"snippet":"… [FOU] The Common Crawl Foundation. Common crawl. URL http://commoncrawl.org. [ALE2019] Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. Language models are unsupervised multitask learners, 2019. …","url":["https://www.i-aida.org/wp-content/uploads/2023/09/AI-Large-Language-Models-and-Un-Educat-v1.0.pdf"]}
{"year":"2023","title":"AI-Assisted Tasks and Materials Development for Language Instruction","authors":["X Kou - Center for Language Technology, 2023"],"snippet":"• Multilingual compacity• Comprehension of Text• Generating Text• Engaging in Conversation with ChatGPT• ChatGPT-based Writing Task• Prompt engineering• An example of Lesson Plan generation• Cautions (errors, etc.)• Alternative tools• Role of …","url":["https://celt.indiana.edu/resources/pedagogical/workshop/ChatGPT-Assisted-Task-Development-2023-September.pdf"]}
{"year":"2023","title":"AI-Augmented Surveys: Leveraging Large Language Models for Opinion Prediction in Nationally Representative Surveys","authors":["J Kim, B Lee - arXiv preprint arXiv:2305.09620, 2023"],"snippet":"How can we use large language models (LLMs) to augment surveys? This paper investigates three distinct applications of LLMs fine-tuned by nationally representative surveys for opinion prediction -- missing data imputation, retrodiction …","url":["https://arxiv.org/pdf/2305.09620"]}
{"year":"2023","title":"AI-based novelty detection in crowdsourced idea spaces","authors":["J Just, T Ströhle, J Füller, K Hutter - Innovation, 2023"],"snippet":"Processing large and heterogeneous numbers of ideas submitted to crowdsourcing contests is a regular challenge for idea evaluators. The aim of this study is to investigate a potential use case for AI-based innovation management and to extend …","url":["https://www.tandfonline.com/doi/pdf/10.1080/14479338.2023.2215740"]}
{"year":"2023","title":"AI-Driven Confidential Computing across Edge-to-Cloud Continuum","authors":["S Zobaed - arXiv preprint arXiv:2301.00928, 2023"],"snippet":"With the meteoric growth of technology, individuals and organizations are widely adopting cloud services to mitigate the burdens of maintenance. Despite its scalability and ease of use, many users who own sensitive data refrain from fully …","url":["https://arxiv.org/pdf/2301.00928"]}
{"year":"2023","title":"AI-Generated Content (AIGC) for Various Data Modalities: A Survey","authors":["LING FOO, JUN LIU - 2023"],"snippet":"Amidst the rapid advancement of artificial intelligence (AI), the development of content generation techniques stands out as one of the most captivating and widely discussed topics in the field. AI-generated content (AIGC) encompasses the …","url":["https://www.researchgate.net/profile/Lin-Geng-Foo/publication/373450974_AI-Generated_Content_AIGC_for_Various_Data_Modalities_A_Survey/links/656ac2b8ce88b87031281ca4/AI-Generated-Content-AIGC-for-Various-Data-Modalities-A-Survey.pdf"]}
{"year":"2023","title":"AI-generated vs human-authored texts: A Multidimensional comparison","authors":["TB Sardinha - Applied Corpus Linguistics, 2023"],"snippet":"The goal of this study is to assess the degree of resemblance between texts generated by artificial intelligence (GPT) and (written and spoken) texts produced by human individuals in real-world settings. A comparative analysis was conducted …","url":["https://www.sciencedirect.com/science/article/pii/S2666799123000436"]}
{"year":"2023","title":"AI-POWERED TEXT ANALYSIS TOOL FOR SENTIMENT ANALYSIS","authors":["D Kebede, N Tesfai - 2023"],"snippet":"In today’s digital era, text data plays a ubiquitous role across various domains. This bachelor’s thesis focuses on the field of sentiment analysis, specifically addressing the task of classifying text into positive, negative, or neutral sentiments with the help …","url":["https://www.diva-portal.org/smash/get/diva2:1765294/FULLTEXT01.pdf"]}
{"year":"2023","title":"AIGC Empowering Telecom Sector White Paper","authors":["Y Ouyang, Y Zhang, X Ye, Y Liu, Y Song, Y Liu, S Bian… - arXiv preprint arXiv …, 2023"],"snippet":"In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world …","url":["https://arxiv.org/pdf/2307.11449"]}
{"year":"2023","title":"ALEXSIS+: Improving Substitute Generation and Selection for Lexical Simplification with Information Retrieval","authors":["K North, A Dmonte, T Ranasinghe, M Shardlow… - … on Innovative Use of NLP for …, 2023"],"snippet":"… We retrieve instances from the CommonCrawl News (CC-News) dataset2 by searching for the 386 English, 381 Spanish, and 386 Portuguese complex words given to the original participants of TSAR-2022. The CC-News dataset contains …","url":["https://aclanthology.org/2023.bea-1.33.pdf"]}
{"year":"2023","title":"Algorithmic bias and discrimination through digitalisation in education","authors":["R Eynon - World Yearbook of Education 2024: Digitalisation of …, 2023"],"snippet":"… One example is the Common-Crawl data set, created by a San Francisco-based non-profit organisation that regularly crawls the web. The size of this and similar data sets is vast: as of April 2021, the Common-Crawl archive was around 320 TB in …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=v67dEAAAQBAJ&oi=fnd&pg=RA10-PA2018-IA3&dq=commoncrawl&ots=FcFZZEVvbX&sig=S1jPzwWzHwuMS6v0BblL76u_tI8"]}
{"year":"2023","title":"Algorithms learn and propagate gender‐biased representations of consumers","authors":["S Rathee, S Banker, A Mishra, H Mishra - Journal of Consumer Psychology"],"snippet":"… In an analysis based on billions of documents from Common Crawl, we build on prior research to illustrate that algorithms can learn gender-biased associations with marketplace-relevant psychographic attributes even when there is no psychological …","url":["https://myscp.onlinelibrary.wiley.com/doi/abs/10.1002/jcpy.1351"]}
{"year":"2023","title":"Algorithms propagate gender bias in the marketplace—with consumers' cooperation","authors":["S Rathee, S Banker, A Mishra, H Mishra"],"snippet":"… In an analysis based on billions of documents from Common Crawl, we build on prior research to illustrate that algorithms can learn genderbiased associations with marketplacerelevant psychographic attributes even when there is no psychological …","url":["https://sachinbanker.com/publications/rathee%20banker%20mishra%20mishra%202023%20algorithms%20propagate%20gender%20bias%20in%20the%20marketplace.pdf"]}
{"year":"2023","title":"Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses","authors":["L Gómez-Zaragozá, S Wills, C Tejedor-Garcia… - arXiv preprint arXiv …, 2023"],"snippet":"… Then, the pre-trained FastText embedding trained on Common Crawl [32] was used to convert the transcriptions of the participants’ responses into word vectors. These representations then were fed into a neural network (NN), composed of a …","url":["https://arxiv.org/pdf/2306.03443"]}
{"year":"2023","title":"AMOE: A Tool to Automatically Extract and Assess Organizational Evidence for Continuous Cloud Audit","authors":["F Deimling, M Fazzolari - IFIP Annual Conference on Data and Applications …, 2023"],"snippet":"The recent spread of cloud services has enabled many companies to take advantage of them. Nevertheless, the main concern about the adoption of cloud services remains the lack of transparency perceived by customers regarding security …","url":["https://link.springer.com/chapter/10.1007/978-3-031-37586-6_22"]}
{"year":"2023","title":"Amplifying Limitations, Harms and Risks of Large Language Models","authors":["M O'Neill, M Connor - arXiv preprint arXiv:2307.04821, 2023"],"snippet":"… We know that GPT-3 was trained on a combination of sources drawn from the wilds of the internet, including Common Crawl data from 2016 to 2019, Webtext, Books and Wikipedia [10]. Analysis of Common Crawl data has shown that it …","url":["https://arxiv.org/pdf/2307.04821"]}
{"year":"2023","title":"An Ambient Intelligence-based Approach For Longitudinal Monitoring of Verbal and Vocal Depression Symptoms","authors":["A Othmani, M Muzammel - arXiv preprint arXiv:2308.08472, 2023"],"snippet":"… For word embedding, we utilize the fastText pretrained network [15], which was trained on Common Crawl 1 and incorporates sub-word information. This network produces word vectors of size 300. In cases where certain words are not present in …","url":["https://arxiv.org/pdf/2308.08472"]}
{"year":"2023","title":"An Analysis on the Basic Technologies of ChatGPT","authors":["Q Li, L Yi, Z Zhixiong, L Xuesi, X Jing, X Qinya, L Yang… - Data Analysis and …, 2023"],"snippet":"[Objective] Review and analyze the corpus, algorithms and models related to ChatGPT, and provide a systematic reference for peer research.[Methods] This paper systematically reviewed the relevant literature and materials since the release …","url":["https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/article/downloadArticleFile.do?attachType=PDF&id=5654"]}
{"year":"2023","title":"An Empirical Comparison of Web Content Extraction Algorithms","authors":["J Bevendorff, S Gupta, J Kiesel, B Stein - 2023"],"snippet":"… Ungoliant uses a FastText [19] language classifier to identify natural-language text in large amounts of web data from the Common Crawl. Although extraction precision is a concern, the focus is clearly on recall. A more specific task than main …","url":["https://webis.de/downloads/publications/papers/bevendorff_2023b.pdf"]}
{"year":"2023","title":"An Empirical Study of Consistency Regularization for End-to-End Speech-to-Text Translation","authors":["P Gao, R Zhang, Z He, H Wu, H Wang - arXiv preprint arXiv:2308.14482, 2023"],"snippet":"Consistency regularization methods, such as R-Drop (Liang et al., 2021) and CrossConST (Gao et al., 2023), have achieved impressive supervised and zero-shot performance in the neural machine translation (NMT) field. Can we also boost end-to-end …","url":["https://arxiv.org/pdf/2308.14482"]}
{"year":"2023","title":"An Ensemble Method to Classify Telugu Idiomatic Sentences using Deep Learning Models","authors":["J Briskilal, CVMS Praneeth, C Chaitanya, MJ Karthik… - … International Conference on …, 2023"],"snippet":"… the English Wikipedia that is utilized in BERT, The extra data included the Common Crawl News dataset, which has 63 million items and 76 gigabytes, the Web text corpus, and the Common Crawl Stories dataset (31 GB) makes the simple …","url":["https://ieeexplore.ieee.org/abstract/document/10134038/"]}
{"year":"2023","title":"An Ensemble-Based Approach for Generative Language Model Attribution","authors":["H Abburi, M Suesserman, N Pudota, B Veeramani… - International Conference on …, 2023"],"snippet":"… xlm-roberta-large-finetuned-conll03-english is XLM-RoBERTa based model [2] which is a large multi-lingual language model trained on 2.5TB of filtered Common Crawl data. The conll03-english model is fine-tuned on the XLM-RoBERTa model …","url":["https://link.springer.com/chapter/10.1007/978-981-99-7254-8_54"]}
{"year":"2023","title":"An Evaluation of Persian-English Machine Translation Datasets with Transformers","authors":["A Sartipi, M Dehghan, A Fatemi - arXiv preprint arXiv:2302.00321, 2023"],"snippet":"Nowadays, many researchers are focusing their attention on the subject of machine translation (MT). However, Persian machine translation has remained unexplored despite a vast amount of research being conducted in languages with high resources …","url":["https://arxiv.org/pdf/2302.00321"]}
{"year":"2023","title":"An Evaluation on Large Language Model Outputs: Discourse and Memorization","authors":["A de Wynter, X Wang, A Sokolov, Q Gu, SQ Chen - arXiv preprint arXiv:2304.08637, 2023"],"snippet":"We present an empirical evaluation of various outputs generated by nine of the most widely-available large language models (LLMs). Our analysis is done with off-the-shelf, readily-available tools. We find a correlation between percentage of memorized text …","url":["https://arxiv.org/pdf/2304.08637"]}
{"year":"2023","title":"An Explainable Ensemble of Multi-View Deep Learning Model for Fake Review Detection","authors":["R Mohawesh, S Xu, M Springer, Y Jararweh… - Journal of King Saud …, 2023"],"snippet":"Online reviews significantly impact consumers who are purchasing or seeking services via the Internet. Businesses and review platforms need to manage these online reviews to avoid misleading customers through fake ones. This necessitates …","url":["https://www.sciencedirect.com/science/article/pii/S1319157823001982"]}
{"year":"2023","title":"An Extractive Question Answering System for the Tamil Language","authors":["A Krishnan, SR Sriram, BVR Ganesan, S Sridhar - Advances in Science and …, 2023"],"snippet":"… This model has been trained on a huge amount of cleaned common crawl data. For low resource languages, new unlabeled corpora were generated. XLM-R is a variant of RoBERTa, which in turn is a variant of BERT [6]. …","url":["https://www.scientific.net/AST.124.312"]}
{"year":"2023","title":"An Improved Framework for Scaling Party Positions from Texts using Transformer and Supervised Dimension Reduction","authors":["HHV Nguyen - 2023"],"snippet":"Previous research in both Natural Language Processing (NLP) and political science has proven the superiority of the Transformer architecture compared to word frequencies and word embeddings on multiple text analysis tasks. In this article, I …","url":["https://osf.io/8sha3/download"]}
{"year":"2023","title":"An improved sentiment classification model based on data quality and word embeddings","authors":["A Siagh, FZ Laallam, O Kazar, H Salem - The Journal of Supercomputing, 2023"],"snippet":"User-generated content on social media platforms has reached big data levels. Sentiment analysis of this data provides opportunities to gain valuable insights into any domain. However, analyzing real-world data may confront the challenge of class …","url":["https://link.springer.com/article/10.1007/s11227-023-05099-1"]}
{"year":"2023","title":"An Integrated Analysis of Multilingual Texts Spanning Dual Alphabets","authors":["FT Аdilova, RR Davronov, RA Safarov - INTERNATIONAL JOURNAL OF …, 2023"],"snippet":"Abstract Language recognition in natural language processing (NLP) aims to determine the specific language of a text or document. As the number of languages increases, this task becomes more complex. This study introduces a detailed model …","url":["http://ijdt.uz/index.php/ijdt/article/download/110/75"]}
{"year":"2023","title":"An Investigation Into Supervision for Seq2Seq Techniques for Natural Language to Code Translation","authors":["MS Yeditha - 2022"],"snippet":"… The dataset that was used to train this was called “Common Crawl”, an open source dataset consisting of nearly a trillion words. On top of this, the authors filtered a version of Common Crawl that was most similar to a range of high-quality corpora …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/49699/Yeditha_washington_0250O_25027.pdf?sequence=1"]}
{"year":"2023","title":"An Investigation of Preference Judging Consistency","authors":["LN Phan Minh - 2023"],"snippet":"Preference judging has been proposed as an effective method to identify the most relevant documents for a given search query. In this thesis, we investigate the degree to which assessors using a preference judging system are able to …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19272/PhanMinh_LinhNhi.pdf?sequence=3&isAllowed=y"]}
{"year":"2023","title":"An Investigation of Representation and Allocation Harms in Contrastive Learning","authors":["S Maity, M Agarwal, M Yurochkin, Y Sun - arXiv preprint arXiv:2310.01583, 2023"],"snippet":"… In this experiment, we study the potential harms of CL applied to data obtained from Common Crawl, a popular source of text data for self-… 2019) which consists of around 400k online biographies in English extracted from the Common Crawl data …","url":["https://arxiv.org/pdf/2310.01583"]}
{"year":"2023","title":"An Open Source Data Contamination Report for Llama Series Models","authors":["Y Li - arXiv preprint arXiv:2310.17589, 2023"],"snippet":"… Our approach utilises a search engine and the Common Crawl index, avoiding the need to host the full 2017-2020 Common Crawl dumps locally. This massive training data would incur prohibitive computational requirements. However, relying …","url":["https://arxiv.org/pdf/2310.17589"]}
{"year":"2023","title":"An Urgency for Inclusivity: Redesigning Datasets for Improved Representation of LGBTQ+ Identity Terms in Artificial Intelligence (AI)","authors":["L Wang - 2023"],"snippet":"… The Common Crawl Dataset stands as a vital resource in the realm of AI model training, … However, despite the Common Crawl's prominence, handling LGBTQ+ identity terms in AI … ’s C4 dataset, a filtered version of the Common Crawl.The …","url":["https://laniwang.com/LaniWangFinalPaper.CORRECTFORMATTING.pdf"]}
{"year":"2023","title":"Analogical Proportions and Creativity: A Preliminary Study","authors":["S Afantenos, H Prade, LC Bernardes - arXiv preprint arXiv:2310.13500, 2023"],"snippet":"Analogical proportions are statements of the form \"$a$ is to $b$ as $c$ is to $d$\", which expresses that the comparisons of the elements in pair $(a, b)$ and in pair $(c, d)$ yield similar results. Analogical proportions are creative in the sense that given 3 …","url":["https://arxiv.org/pdf/2310.13500"]}
{"year":"2023","title":"ANALOGICAL--A New Benchmark for Analogy of Long Text for Large Language Models","authors":["T Wijesiriwardene, R Wickramarachchi, BG Gajera… - arXiv preprint arXiv …, 2023"],"snippet":"… In addition three other corpora containing news articles, web content, and a filtered subset of the CommonCrawl corpus were used. The training approach of RoBERTa differs from BERT as follows. RoBERTa modifies the MLM task by moving …","url":["https://arxiv.org/pdf/2305.05050"]}
{"year":"2023","title":"Analysing Cross-Lingual Transfer in Low-Resourced African Named Entity Recognition","authors":["M Beukman, M Fokam - arXiv preprint arXiv:2309.05311, 2023"],"snippet":"Transfer learning has led to large gains in performance for nearly all NLP tasks while making downstream models easier and faster to train. This has also been extended to low-resourced languages, with some success. We investigate the …","url":["https://arxiv.org/pdf/2309.05311"]}
{"year":"2023","title":"ANALYSIS OF A DECISION SUPPORT SYSTEM USING AHP FOR FOOD AND RESTAURANT SELECTION BASED ON THE USER'S FOOD CRAVINGS AND …","authors":["D Dyondra, J Purnama, M Galinium - SGU Online Thesis Submission, 2023"],"snippet":"The purpose of this research is to develop a decision support system (DSS) using the AHP algorithm for selecting restaurants based on the user's food cravings and location in Jakarta. The data for the DSS was gathered by scraping restaurant data …","url":["https://thesis.sgu.ac.id/index.php/ots/article/download/4498/832"]}
{"year":"2023","title":"Analysis of ChatGPT as a Question-Answering Tool","authors":["P Pichappan, M Krishnamurthy, P Vijayakumar - Journal of Digital Information …, 2023"],"snippet":"… Its data sources are drawn from Common Crawl (a non-profit organisation that crawls the web data and makes it available to open the stored information and data volume open), WebText2, Books and Wikipedia. WebText2 is the extraction of the …","url":["https://www.researchgate.net/profile/Pit-Pichappan/publication/371686172_Analysis_of_ChatGPT_as_a_Question-Answering_Tool/links/6490113f8de7ed28ba3c1c38/Analysis-of-ChatGPT-as-a-Question-Answering-Tool.pdf"]}
{"year":"2023","title":"Analysis of Deep Learning Model Combinations and Tokenization Approaches in Sentiment Classification","authors":["A Erkan, T Güngör - IEEE Access, 2023"],"snippet":"Sentiment classification is a natural language processing task to identify opinions expressed in texts such as product or service reviews. In this work, we analyze the effects of different deep-learning model combinations, embedding methods, and …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10332170.pdf"]}
{"year":"2023","title":"Analysis of Digital Information in Storage Devices Using Supervised and Unsupervised Natural Language Processing Techniques","authors":["LA Martínez Hernández, AL Sandoval Orozco… - Future Internet, 2023"],"snippet":"… Sources supplementing the training data include news data (CommonCrawl news, 76 GB), text from websites (38 GB), and stories (31 GB). The training of this data is performed over the course of a day using the latest generation graphics card. This …","url":["https://www.mdpi.com/1999-5903/15/5/155"]}
{"year":"2023","title":"Analysis of Fake News Detection Methods","authors":["M Amjad, O Vitman, G Sidorov, A Zhila, A Gelbukh - … : Selected Papers of the 8th World …, 2023"],"snippet":"The fact that it might be difficult to distinguish between real news and fake news is of the utmost significance. It is difficult, time-consuming, and expensive to manually review enormous volumes of digital data in order to detect false news, which is …","url":["https://link.springer.com/chapter/10.1007/978-3-031-23476-7_13"]}
{"year":"2023","title":"Analysis of Machine Learning and Deep Learning Algorithms for Text Sentiment Detection","authors":["S Dimitrijević"],"snippet":"Sentiment analysis or opinion mining is the task of automatically extracting and classifying the sentiment of the text. It can be applied in numerous fields such as marketing, customer service, etc. Sentiment analysis has gained much attention in …","url":["https://matematika.pmf.uns.ac.rs/wp-content/uploads/2023/02/StefanDimitrijevic.pdf"]}
{"year":"2023","title":"Analysis of the Evolution of Advanced Transformer-Based Language Models: Experiments on Opinion Mining","authors":["NE Zekaoui, S Yousfi, M Rhanoui, M Mikram - arXiv preprint arXiv:2308.03235, 2023"],"snippet":"… However, the multilingual version of RoBERTa [15] called XLM-RoBERTa [21], pre-trained on the newly created 2.5TB multilingual CommonCrawl corpus containing 100 different languages, has further pushed the performance. It has shown strong …","url":["https://arxiv.org/pdf/2308.03235"]}
{"year":"2023","title":"Analysis of the Performance Impact of Fine-Tuned Machine Learning Model for Phishing URL Detection","authors":["SR Abdul Samad, S Balasubaramanian, AS Al-Kaabi… - Electronics, 2023"],"snippet":"… Alexa and Common Crawl are used to compile lists of legitimate websites; whereas Phish-Tank and OpenPhish are used to compile lists of malicious ones. Binary labels, such as 0 for legitimate and 1 for phishing, are present in this dataset …","url":["https://www.mdpi.com/2079-9292/12/7/1642/pdf"]}
{"year":"2023","title":"Analysis of the Semantic Shift in Diachronic Word Embeddings for Spanish Before and After COVID-19","authors":["ER Betancourt, EC Murillo - CLEI Electronic Journal, 2023"],"snippet":"… In this work, we analyzed millions of Spanish web pages collected by the CommonCrawl … The documents were downloaded from CommonCrawl, discarding the documents with less … 2018 and week 25 of 2021 were downloaded …","url":["https://clei.org/cleiej/index.php/cleiej/article/download/593/455"]}
{"year":"2023","title":"Analysis of the Technical Principles of ChatGPT and Prospects for Pre-trained Large Models","authors":["Z Jin - 2023 IEEE 3rd International Conference on Information …, 2023"],"snippet":"ChatGPT is a pre-trained model in the field of natural language processing. As a generative model, the technical foundation of ChatGPT is a deep learning model called the \"Generative Adversarial Network\". The pre-trained large model …","url":["https://ieeexplore.ieee.org/abstract/document/10165540/"]}
{"year":"2023","title":"Analyzing and Improving the Scalability of In-Memory Indices for Managed Search Engines","authors":["A Chilukuri, S Akram - 2023"],"snippet":"… We create indices of various sizes using the January 2022 CommonCrawl data set [43], a large repository of web crawl data. Index size in Lucene is difficult to control precisely. We, therefore, index … https://commoncrawl.org/2022/06/may-2022-crawl-archivenow-available/ …","url":["https://shbakram.github.io/assets/papers/ismm2023-lucene.pdf"]}
{"year":"2023","title":"Analyzing Failure Modes of Inscrutable Machine Learning Models","authors":["A Olmo Hernandez - 2022"],"snippet":"ABSTRACT Machine learning models and in specific, neural networks, are well known for being inscrutable in nature. From image classification tasks and generative techniques for data augmentation, to general purpose natural language …","url":["https://keep.lib.asu.edu/_flysystem/fedora/c7/OlmoHernandez_asu_0010E_22349.pdf"]}
{"year":"2023","title":"Analyzing Syntactic Generalization Capacity of Pre-trained Language Models on Japanese Honorific Conversion","authors":["R Sekizawa, H Yanaka - arXiv preprint arXiv:2306.03055, 2023"],"snippet":"Using Japanese honorifics is challenging because it requires not only knowledge of the grammatical rules but also contextual information, such as social relationships. It remains unclear whether pre-trained large language models (LLMs) can flexibly …","url":["https://arxiv.org/pdf/2306.03055"]}
{"year":"2023","title":"Analyzing Text Representations by Measuring Task Alignment","authors":["C Gonzalez-Gutierrez, A Primadhanty, F Cazzaro… - arXiv preprint arXiv …, 2023"],"snippet":"Textual representations based on pre-trained language models are key, especially in few-shot learning scenarios. What makes a representation good for text classification? Is it due to the geometric properties of the space or because it is well …","url":["https://arxiv.org/pdf/2305.19747"]}
{"year":"2023","title":"Analyzing the Impact of Tokenization on Multilingual Epidemic Surveillance in Low-Resource Languages","authors":["S Mutuvi, E Boros, A Doucet, G Lejeune, A Jatowt… - International Conference on …, 2023"],"snippet":"… On the other hand, XLM-RoBERTa is pre-trained on 2.5TB of CommonCrawl data covering 100 languages. As a result, when compared to Wikipedia data, CommonCrawl data is significantly larger, effectively increasing the available …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41682-8_2"]}
{"year":"2023","title":"Analyzing the unrestricted web: The finnish corpus of online registers","authors":["V Skantsi, V Laippala - Nordic Journal of Linguistics, 2023"],"snippet":"… Second, Finnish documents were identified and retrieved from Common Crawl, an organization that crawls the Internet providing its archives and datasets for public use (https://commoncrawl.org/). Texts were cleaned from menus and listings with …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/BDCA0FE03ABD9087CC5652533880C8C0/S0332586523000021a.pdf/div-class-title-analyzing-the-unrestricted-web-the-finnish-corpus-of-online-registers-div.pdf"]}
{"year":"2023","title":"and JR Orozco-ArroyaveD","authors":["D Escobar-Grisales, SA Moreno-Acevedo… - Applied Computer Sciences in …"],"snippet":"… This model was pre-trained with 2.5 TB of text data from the Common Crawl corpus [17], which includes text in 100 different languages. This extensive pre-training has allowed RoBERTa to compute text representations in multiple languages …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=fJ3fEAAAQBAJ&oi=fnd&pg=PA173&dq=commoncrawl&ots=Sbvy8lnigr&sig=WChAuY_i09PQ0f7N959Xx1wlsB4"]}
{"year":"2023","title":"Annotation for computational argumentation analysis: Issues and perspectives","authors":["A Lindahl, L Borin - Language and Linguistics Compass, 2024"],"snippet":"Abstract Argumentation has long been studied in a number of disciplines, including several branches of linguistics. In recent years, computational processing of argumentation has been added to the list, reflecting a general interest from the field …","url":["https://compass.onlinelibrary.wiley.com/doi/pdf/10.1111/lnc3.12505"]}
{"year":"2023","title":"Anonymity at Risk? Assessing Re-Identification Capabilities of Large Language Models","authors":["A Nyffenegger, M Stürmer, J Niklaus - arXiv preprint arXiv:2308.11103, 2023"],"snippet":"Anonymity of both natural and legal persons in court rulings is a critical aspect of privacy protection in the European Union and Switzerland. With the advent of LLMs, concerns about large-scale re-identification of anonymized persons are growing. In …","url":["https://arxiv.org/pdf/2308.11103"]}
{"year":"2023","title":"ANSEL Photobot: A Robot Event Photographer with Semantic Intelligence","authors":["D Rivkin, G Dudek, N Kakodkar, D Meger, O Limoyo… - arXiv preprint arXiv …, 2023"],"snippet":"Our work examines the way in which large language models can be used for robotic planning and sampling, specifically the context of automated photographic documentation. Specifically, we illustrate how to produce a photo-taking robot with …","url":["https://arxiv.org/pdf/2302.07931"]}
{"year":"2023","title":"App2Check at EMit: Large Language Models for Multilabel Emotion Classification","authors":["G Cageggi, E Di Rosa, A Uboldi - 2023"],"snippet":"In this paper we compare the performance of three state-of-the-art LLM-based approaches for multilabel emotion classification: fine-tuned multilingual T5 and two few shot prompting approaches: plain FLAN and ChatGPT. In our experimental …","url":["https://ceur-ws.org/Vol-3473/paper3.pdf"]}
{"year":"2023","title":"Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review","authors":["H De Rosario, S Pitarch-Corresa, I Pedrosa… - JMIR Medical Informatics, 2023"],"snippet":"… maturity of more complex representations of language data, such as the word embeddings into large-dimensional numeric vectors and their effective processing through deep neural networks, as well as the exploitation of huge databases of texts …","url":["https://medinform.jmir.org/2023/1/e48693"]}
{"year":"2023","title":"Ar-PuFi: A Short-Text Dataset to Identify the Offensive Messages Towards Public Figures in the Arabian Community","authors":["M Abdelhakim, B Liu, C Sun - Expert Systems with Applications, 2023"],"snippet":"The fight against offensive speech on the Internet necessitates increased efforts from linguistic analysis and artificial intelligence perspectives to develop countermeasures and preventive methods. Reliable predictions can only be …","url":["https://www.sciencedirect.com/science/article/pii/S0957417423013908"]}
{"year":"2023","title":"Arabic Mini-ClimateGPT: A Climate Change and Sustainability Tailored Arabic LLM","authors":["S Mullappilly, A Shaker, O Thawakar, H Cholakkal… - Findings of the Association …, 2023"],"snippet":"Climate change is one of the most significant challenges we face together as a society. Creating awareness and educating policy makers the wide-ranging impact of climate change is an essential step towards a sustainable future. Recently, Large …","url":["https://aclanthology.org/2023.findings-emnlp.941.pdf"]}
{"year":"2023","title":"Arabic Tweets-Based Sentiment Analysis to Investigate the Impact of COVID-19 in KSA: A Deep Learning Approach","authors":["A Alqarni, A Rahman - Big Data and Cognitive Computing, 2023"],"snippet":"… The FastText model was also trained by [68] on Wikipedia and common crawl used the CBOW architecture. The results of the comparison between all pre-trained word embeddings for all datasets in two periods are shown in Table 7 and Table 8. …","url":["https://www.mdpi.com/2070176"]}
{"year":"2023","title":"AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing","authors":["A Alghamdi, X Duan, W Jiang, Z Wang, Y Wu, Q Xia… - arXiv preprint arXiv …, 2023"],"snippet":"Developing monolingual large Pre-trained Language Models (PLMs) is shown to be very successful in handling different tasks in Natural Language Processing (NLP). In this work, we present AraMUS, the largest Arabic PLM with 11B parameters trained …","url":["https://arxiv.org/pdf/2306.06800"]}
{"year":"2023","title":"AraProp at WANLP 2022 Shared Task: Leveraging Pre-Trained Language Models for Arabic Propaganda Detection","authors":["GS Tomar - Proceedings of the The Seventh Arabic Natural …, 2022"],"snippet":"This paper presents the approach taken for the shared task on Propaganda Detection in Arabic at the Seventh Arabic Natural Language Processing Workshop (WANLP 2022). We participated in Sub-task 1 where the text of a tweet is provided, and the …","url":["https://aclanthology.org/2022.wanlp-1.56.pdf"]}
{"year":"2023","title":"Are Large Language Models Fit For Guided Reading?","authors":["P Ochieng - arXiv preprint arXiv:2305.10645, 2023"],"snippet":"This paper looks at the ability of large language models to participate in educational guided reading. We specifically, evaluate their ability to generate meaningful questions from the input text, generate diverse questions both in terms of content …","url":["https://arxiv.org/pdf/2305.10645"]}
{"year":"2023","title":"Are Large Language Models Geospatially Knowledgeable?","authors":["P Bhandari, A Anastasopoulos, D Pfoser - arXiv preprint arXiv:2310.13002, 2023"],"snippet":"… [29] by processing Commoncrawl 6 snapshots. Given that the LLaMA model was trained directly on Commoncrawl snapshots, we believe that CC100 is a good approximation of the training data. We conduct an analysis similar to Elazar et al. [7] …","url":["https://arxiv.org/pdf/2310.13002"]}
{"year":"2023","title":"Argot as a Trust Signal: Slang, Jargon & Reputation on a Large Cybercrime Forum","authors":["J Hughes, A Caines, A Hutchings"],"snippet":"… Using the FastText models trained on CommonCrawl and HackForums data, we obtain word embeddings for all tokens in the HackForums dataset which have over 100 occurrences across all posts (including multiple usage in a post). We threshold …","url":["https://weis2023.econinfosec.org/wp-content/uploads/sites/11/2023/06/weis23-hughes.pdf"]}
{"year":"2023","title":"ArgU: A Controllable Factual Argument Generator","authors":["S Saha, R Srihari - arXiv preprint arXiv:2305.05334, 2023"],"snippet":"Effective argumentation is essential towards a purposeful conversation with a satisfactory outcome. For example, persuading someone to reconsider smoking might involve empathetic, well founded arguments based on facts and expert …","url":["https://arxiv.org/pdf/2305.05334"]}
{"year":"2023","title":"ArguGPT: evaluating, understanding and identifying argumentative essays generated by GPT models","authors":["Y Liu, Z Zhang, W Zhang, S Yue, X Zhao, X Cheng… - arXiv preprint arXiv …, 2023"],"snippet":"AI generated content (AIGC) presents considerable challenge to educators around the world. Instructors need to be able to detect such text generated by large language models, either with the naked eye or with the help of some tools. There is …","url":["https://arxiv.org/pdf/2304.07666"]}
{"year":"2023","title":"Argumentation Element Annotation Modeling using XLNet","authors":["C Ormerod, A Burkhardt, M Young, S Lottridge - arXiv preprint arXiv:2311.06239, 2023"],"snippet":"This study demonstrates the effectiveness of XLNet, a transformer-based language model, for annotating argumentative elements in persuasive essays. XLNet's architecture incorporates a recurrent mechanism that allows it to model long-term …","url":["https://arxiv.org/pdf/2311.06239"]}
{"year":"2023","title":"Artificial cheerleading in IEO: Marketing campaign or pump and dump scheme","authors":["Y Tian, Y Xie - Information Processing & Management, 2024"],"snippet":"… XLM-R, on the other hand, was trained on a newly curated and clean CommonCrawl dataset spanning 2.5 TB in 100 different languages. The model has surpassed previous multilingual models like mBERT and XLM in tasks such as …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323002741"]}
{"year":"2023","title":"Artificial Intelligence (AI) Art Generators in the Architectural Design Curricula","authors":["KE Hedges - 2023 ASEE Annual Conference & Exposition, 2023"],"snippet":"… A web crawler, such as the non-profit Common Crawl, is a bot that trolls and scrapes the web for … Schäfer, “CommonCOW: Massively Huge Web Corpora from CommonCrawl Data and a Method to Distribute them Freely under Restrictive EU …","url":["https://peer.asee.org/artificial-intelligence-ai-art-generators-in-the-architectural-design-curricula.pdf"]}
{"year":"2023","title":"Artificial Intelligence and Librarianship","authors":["M Frické - 2023"],"snippet":"Artificial Intelligence and Librarianship: Page 1 Martin Frické Artificial Intelligence and Librarianship: Notes for Teaching Page 2 2 Martin Frické, Professor Emeritus School of Information The University of Arizona, Tucson, AZ, USA mfricke@arizona.edu …","url":["https://softoption.us/sites/default/files/AIinLibrariesContentsBibliography.pdf"]}
{"year":"2023","title":"Artificial intelligence applications in technical communication for the optimization of content management processes","authors":["KB Hanczaryk, W Ziegler - AIP Conference Proceedings, 2023"],"snippet":"… The training was done on texts from Wikipedia and Common Crawl. The vocabulary of the model includes nearly 4,947,000 words, each represented by a vector of length 100 [21, 22]. The similarity of words can be determined by the …","url":["https://pubs.aip.org/aip/acp/article/2909/1/100007/2924885"]}
{"year":"2023","title":"Artificial intelligence as a tool in social media content moderation","authors":["E Lagren - 2023"],"snippet":"On social media, users engage with each other through consuming and creating user-generated content, the amount of which has increased alongside the growth of the userbase. This presents challenges to social media companies as some …","url":["https://jyx.jyu.fi/bitstream/handle/123456789/92439/1/URN%3ANBN%3Afi%3Ajyu-202312218433.pdf"]}
{"year":"2023","title":"Artificial Intelligence for Business Creativity","authors":["M Pagani, R Champion - 2023"],"snippet":"Artificial Intelligence for Business Creativity provides an in-depth examination of the integration of Artificial Intelligence (AI) into the business sector to foster creativity. The book explores the interplay between micro-level individual creativity and macro-level …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=zMDGEAAAQBAJ&oi=fnd&pg=PA1928&dq=commoncrawl&ots=VIVepH3-f5&sig=Ka_aQtw10I2vx6OcRaFvgzBeiWw"]}
{"year":"2023","title":"Artificial intelligence literacy for the language industry–with particular emphasis on recent large language models such as GPT-4","authors":["R Krüger - Lebende Sprachen, 2023"],"snippet":"This article explores the concept of artificial intelligence (AI) literacy in the context of the language industry, placing particular emphasis on recent large language models such as GPT-4. After a brief introduction in which the relevance of AI literacy in the …","url":["https://www.degruyter.com/document/doi/10.1515/les-2023-0024/html"]}
{"year":"2023","title":"Artificial Intelligent based Models for Event Extraction using Customer Support Applications","authors":["M Mayuranathan, G Akilandasowmya, B Jayaram… - 2023 Second International …, 2023"],"snippet":"… text corpora like Wikipedia and Common Crawl are popular options for computer vision and natural language processing jobs, respectively. Prepare for pretrained models by designing the architecture of the base network. Common choices include …","url":["https://ieeexplore.ieee.org/abstract/document/10250679/"]}
{"year":"2023","title":"Artificial Neural Networks: A Noticeable Evolution in AI","authors":["P Sarang - Thinking Data Science: A Data Science Practitioner's …, 2023"],"snippet":"Artificial neural networks (ANN) surely brought a noticeable evolution to the AI field. A data scientist has now a choice between the two techniques—GOFAI and ANN, while designing a machine learning model. In this chapter, I introduce you to this …","url":["https://link.springer.com/chapter/10.1007/978-3-031-02363-7_17"]}
{"year":"2023","title":"Artificially Intelligent Billing in Spine Surgery: An Analysis of a Large Language Model","authors":["B Zaidat, YS Lahoti, A Yu, KS Mohamed, SK Cho… - Global Spine Journal, 2023"],"snippet":"Study Design Retrospective cohort study. Objectives This study assessed the effectiveness of a popular large language model, ChatGPT-4, in predicting Current Procedural Terminology (CPT) codes from surgical operative notes. By employing a …","url":["https://journals.sagepub.com/doi/full/10.1177/21925682231224753"]}
{"year":"2023","title":"Asking Questions: an Innovative Way to Interact with Oral History Archives","authors":["A Frémund, M Bulín, J Švec, F Polák - 2023"],"snippet":"… As a speech recognizer, we trained the recent Wav2Vec 2.0 end-to-end model with a lower-case n-gram language model estimated from CommonCrawl data. In addition, the raw output of the speech recognizer was post-processed using …","url":["https://dspace5.zcu.cz/bitstream/11025/54621/1/proceedings_svk_2023-42-43.pdf"]}
{"year":"2023","title":"Aspect-Category based Sentiment Analysis with Unified Sequence-To-Sequence Transfer Transformers","authors":["D Van Thin, NLT Nguyen - VNU Journal of Science: Computer Science and …, 2023"],"snippet":"… While the BARTPho and its variants were trained on 20GB of news data, the viT5 models were trained on 71GB of Common Crawl data (a subset of CC100 corpus [19]) for Vietnamese language. Moreover, the text in the CC100 corpus is crawled in the …","url":["https://jcsce.vnu.edu.vn/index.php/jcsce/article/view/662/182"]}
{"year":"2023","title":"Assessing LLMs for Moral Value Pluralism","authors":["N Benkler, D Mosaphir, S Friedman, A Smart… - arXiv preprint arXiv …, 2023"],"snippet":"The fields of AI current lacks methods to quantitatively assess and potentially alter the moral values inherent in the output of large language models (LLMs). However, decades of social science research has developed and refined widely-accepted …","url":["https://arxiv.org/pdf/2312.10075"]}
{"year":"2023","title":"Assessing the Ability of ChatGPT to Screen Articles for Systematic Reviews","authors":["E Syriani, I David, G Kumar - arXiv preprint arXiv:2307.06464, 2023"],"snippet":"… ChatGPT is a Generative Pretrained Transformer that employs an auto-regressive language model trained on large datasets with billions of tokens from CommonCrawl, Wikipedia, and other publicly available text sources. It relies on a deep neural …","url":["https://arxiv.org/pdf/2307.06464"]}
{"year":"2023","title":"Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMT","authors":["B Wolleb, R Silvestri, G Vernikos, LDA Popescu-Belis - arXiv preprint arXiv …, 2023"],"snippet":"Subword tokenization is the de facto standard for tokenization in neural language models and machine translation systems. Three advantages are frequently cited in favor of subwords: shorter encoding of frequent tokens, compositionality of subwords …","url":["https://arxiv.org/pdf/2306.01393"]}
{"year":"2023","title":"Assessing the research landscape and clinical utility of large language models: A scoping review","authors":["YJ Park, A Pillai, J Deng, E Guo, M Gupta, M Paget… - 2023"],"snippet":"… Introduced in November 2022, ChatGPT was trained using large web corpora, including CommonCrawl, WebText, and Wikipedia, as well as internet-based book corpora spanning multiple languages [3]. GPT, along with other popular LLMs such …","url":["https://www.researchsquare.com/article/rs-3472000/latest.pdf"]}
{"year":"2023","title":"Assessing the Value of ChatGPT for Clinical Decision Support Optimization","authors":["S Liu, AP Wright, BL Patterson, JP Wanderer, RW Turer… - medRxiv, 2023"],"snippet":"Objective: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. Methods: We supplied summaries of CDS logic to …","url":["https://www.medrxiv.org/content/medrxiv/early/2023/02/23/2023.02.21.23286254.full.pdf"]}
{"year":"2023","title":"Assessing Translation capabilities of Large Language Models involving English and Indian Languages","authors":["V Mujadia, A Urlana, Y Bhaskar, PA Pavani, K Shravya… - arXiv preprint arXiv …, 2023"],"snippet":"Generative Large Language Models (LLMs) have achieved remarkable advancements in various NLP tasks. In this work, our aim is to explore the multilingual capabilities of large language models by using machine translation as a …","url":["https://arxiv.org/pdf/2311.09216"]}
{"year":"2023","title":"Assessing Vulnerability from Its Description","authors":["Z Zhang, V Kumar, M Mayo, A Bifet - … , UbiSec 2022, Zhangjiajie, China, December 28 …, 2023"],"snippet":"This paper shows an end-to-end Artificial Intelligence (AI) system to estimate the severity level and the various Common Vulnerability Scoring System (CVSS) components from natural language descriptions without reproducing the vulnerability …","url":["https://link.springer.com/chapter/10.1007/978-981-99-0272-9_9"]}
{"year":"2023","title":"Assessment on trial? ChatGPT and the new frontiers of learning and assessment in higher education","authors":["O Kolade, A Owoseni, A Egbetokun"],"snippet":"ChatGPT, a state-of-the-art chatbot built upon Open AI’s generative pre-trained transformer (GPT-3), has generated a major public interest and caused quite a stir in the higher education sector, where reactions have ranged from excitement to …","url":["https://www.researchgate.net/profile/Oluwaseun-Kolade/publication/369974458_Assessment_on_trial_ChatGPT_and_the_new_frontiers_of_learning_and_assessment_in_higher_education/links/64376dc720f25554da29ad9f/Assessment-on-trial-ChatGPT-and-the-new-frontiers-of-learning-and-assessment-in-higher-education.pdf"]}
{"year":"2023","title":"At the intersection of humanity and technology: a technofeminist intersectional critical discourse analysis of gender and race biases in the natural language processing …","authors":["P Barea, D Boeren, JF Ferreira Goncalves - AI & SOCIETY, 2023"],"snippet":"Algorithmic biases, or algorithmic unfairness, have been a topic of public and scientific scrutiny for the past years, as increasing evidence suggests the pervasive assimilation of human cognitive biases and stereotypes in such systems. This …","url":["https://link.springer.com/article/10.1007/s00146-023-01804-z"]}
{"year":"2023","title":"AT WHICH TRAINING STAGE DOES CODE DATA HELP LLMS REASONING?","authors":["Y Ma, Y Liu, Y Yu, Y Zhang, Y Jiang, C Wang, S Li"],"snippet":"… For example, LLaMA was trained with 1.4 trillion tokens consisting of texts (CommonCrawl, C4) and codes (GitHub). These large-scale data with … To improve the data quality, we adopt the following rule-based text cleaning strategies over the raw web pages …","url":["https://arxiv.org/pdf/2309.16298"]}
{"year":"2023","title":"ATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science","authors":["S Munikoti, A Acharya, S Wagle, S Horawalavithana - arXiv preprint arXiv:2311.12289, 2023"],"snippet":"… We took the original ATLAS model as a baseline, which is pretrained with common crawl (CC) and Wikipedia on top of the T5 model. In addition to this pretrained ATLAS, we also leverage ATLAS-Science model from scratch with the …","url":["https://arxiv.org/pdf/2311.12289"]}
{"year":"2023","title":"Attribute Ambiguity Discovery: A Deep Learning Approach via Unsupervised Learning","authors":["E Veltri, G Badaro, M Saeed, P Papotti - 2023"],"snippet":"… Typically, these models are pre-trained on large text corpora such as articles from Wikipedia, news articles, or Common Crawl. The model is pre-trained in an unsupervised manner, for example by predicting a missing token or the next-sentence …","url":["https://ceur-ws.org/Vol-3478/paper40.pdf"]}
{"year":"2023","title":"Audio is all in one: speech-driven gesture synthetics using WavLM pre-trained model","authors":["F Zhang, N Ji, F Gao, S Zhao, Z Wang, S Li - arXiv preprint arXiv:2308.05995, 2023"],"snippet":"… [30] obtain the word embeddings using the GloVe model pre-trained on the Common Crawl corpus [31]. This method marginally outperformed other similar-dimensional embedding models, such as Word2Vec [32] and FastText [33], and had similar …","url":["https://arxiv.org/pdf/2308.05995"]}
{"year":"2023","title":"Augmenters at SemEval-2023 Task 1: Enhancing CLIP in Handling Compositionality and Ambiguity for Zero-Shot Visual WSD through Prompt Augmentation and Text …","authors":["J Li, YT Shiue, YS Shih, J Geiping - Proceedings of the The 17th International …, 2023"],"snippet":"This paper describes our zero-shot approachesfor the Visual Word Sense Disambiguation (VWSD) Task in English. Our preliminarystudy shows that the simple approach of match-ing candidate images with the phrase usingCLIP suffers …","url":["https://aclanthology.org/2023.semeval-1.5.pdf"]}
{"year":"2023","title":"Augmenting interpretable models with large language models during training","authors":["C Singh, A Askari, R Caruana, J Gao - Nature Communications, 2023"],"snippet":"… We compare Aug-Linear to four interpretable baseline models: Bag of ngrams, TF-IDF (Term frequency-inverse document frequency) 23 , GloVE 24 (we use the pre-trained Glove embeddings trained on Common Crawl containing 840 billion tokens, 2.2 …","url":["https://www.nature.com/articles/s41467-023-43713-1"]}
{"year":"2023","title":"Augmenting product knowledge graphs with subjective information","authors":["JM SILVA - 2023"],"snippet":"… The authors scale the pre-training of the models either by increasing the number of parameters (up to 11 Billion) and with a large heuristically cleaned corpus from the Common Crawl web dump3. This final pre-trained dataset, called Colossal …","url":["https://repositorio.ufpe.br/bitstream/123456789/49464/1/TESE%20Johny%20Moreira%20da%20Silva.pdf"]}
{"year":"2023","title":"AugTriever: Unsupervised Dense Retrieval by Scalable Data Augmentation","authors":["R Meng, Y Liu, S Yavuz, D Agarwal, L Tu, N Yu…"],"snippet":"… We apply those methods on Wikipedia passages and CommonCrawl web documents to obtain two large augmented AUGQ datasets. Then we train bi-encoder dense retrievers (using either InBatch or MoCo architecture) using AUGQ and we …","url":["https://openreview.net/pdf?id=-XaFHEKaUJ"]}
{"year":"2023","title":"AUTOCAST++: ENHANCING WORLD EVENT PREDIC","authors":["Q Yan, R Seraj, J He, L Meng, T Sylvain - arXiv preprint arXiv:2310.01880, 2023"],"snippet":"… news articles from the Common Crawl corpus1 spanning 2016 to 2022 for retrieval purpose. For performance evaluation, we use accuracy metrics for T/F and MCQ questions and absolute 1Common Crawl - Open Repository of Web Crawl Data …","url":["https://arxiv.org/pdf/2310.01880"]}
{"year":"2023","title":"Autoencoder for fraudulent transactions data feature engineering","authors":["D Breskuvienė, G Dzemyda - DAMSS: 13th conference on data analysis methods for …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:150999090/150999090.pdf"]}
{"year":"2023","title":"Automated Interpretation of Place Descriptions: Determining Entity Types for Querying OSM","authors":["M Yousaf, T Schwartz, D Wolter - KI-Künstliche Intelligenz, 2023"],"snippet":"This paper is concerned with interpretation of natural language place descriptions, as they are a rich source of geographic information. A place description is interpreted by matching geographic entities occurring in the text against the …","url":["https://link.springer.com/article/10.1007/s13218-022-00798-y"]}
{"year":"2023","title":"Automated programming, symbolic computation, machine learning: my personal view","authors":["B Buchberger - Annals of Mathematics and Artificial Intelligence, 2023"],"snippet":"In this note, I present my personal view on the interaction of the three areas Automated Programming, Symbolic Computation, and Machine Learning. Programming is the activity of finding a (hopefully) correct program (algorithm) for a …","url":["https://link.springer.com/content/pdf/10.1007/s10472-023-09894-7.pdf"]}
{"year":"2023","title":"Automated Short Answer Grading using BERT on German datasets","authors":["S Nath, B Parsaeifard, E Werlen"],"snippet":"Owing to a growth in online learning, the interest in automated grading has intensified, especially due to scoring time reduction. The aim of automated grading is to approximate human level scoring. Automated Short Answer Grading (ASAG) is …","url":["https://www.researchgate.net/profile/Egon-Werlen/publication/373556564_Automated_Short_Answer_Grading_using_BERT_on_German_datasets/links/64f1b6cc4a2a2214db2f1f45/Automated-Short-Answer-Grading-using-BERT-on-German-datasets.pdf"]}
{"year":"2023","title":"Automated Testing and Improvement of Named Entity Recognition Systems","authors":["B Yu, Y Hu, Q Mang, W Hu, P He - arXiv preprint arXiv:2308.07937, 2023"],"snippet":"… Common Crawl,1 a nonprofit organization that crawls the web and freely provides its archives and datasets to the public, has collected 380 TB of data and 3.15 billion pages by October 2022. As of 30 December 2022, there are 6,594,544 articles in the …","url":["https://arxiv.org/pdf/2308.07937"]}
{"year":"2023","title":"Automated Text Identification: Multilingual Transformer-based Models Approach","authors":["G Gritsay, A Grabovoy, A Kildyakov, Y Chekhovich - 2023"],"snippet":"This paper describes our solution approach for the AuTexTification (Automated Text Identification) competition held as part of the IberLEF 2023 conference. Generated text is an increasing problem nowadays. Due to the spread of large volumes of …","url":["https://ceur-ws.org/Vol-3496/autextification-paper15.pdf"]}
{"year":"2023","title":"Automatic Analysis of Peer Feedback using Machine Learning and Explainable Artificial Intelligence","authors":["K Huang - 2023"],"snippet":"Peer assessment is a process where learners evaluate and provide feedback on one another’s performance, which is critical to the student learning process. Earlier research has shown that it can improve student learning outcomes in various settings …","url":["https://www.diva-portal.org/smash/get/diva2:1763088/FULLTEXT01.pdf"]}
{"year":"2023","title":"Automatic Anonymization of Swiss Federal Supreme Court Rulings","authors":["J Niklaus, R Mamié, M Stürmer, D Brunner, M Gygli - arXiv preprint arXiv:2310.04632, 2023"],"snippet":"Releasing court decisions to the public relies on proper anonymization to protect all involved parties, where necessary. The Swiss Federal Supreme Court relies on an existing system that combines different traditional computational methods with …","url":["https://arxiv.org/pdf/2310.04632"]}
{"year":"2023","title":"Automatic classification and prioritisation of actionable BI-RADS categories using natural language processing models","authors":["P López-Úbeda, T Martín-Noguerol, A Luna - Clinical Radiology, 2023"],"snippet":"Aim To facilitate the routine tasks performed by radiologists in their evaluation of breast radiology reports, by enhancing the communication of relevant results to referring physicians via a natural language processing (NLP)-based system to …","url":["https://www.sciencedirect.com/science/article/pii/S0009926023004233"]}
{"year":"2023","title":"Automatic Construction Hazard Identification Integrating On-Site Scene Graphs with Information Extraction in Outfield Test","authors":["X Liu, X Jing, Q Zhu, W Du, X Wang - Buildings, 2023"],"snippet":"… We initialize the word embeddings for the objects and predicates with pre-trained two million word vectors fastText learned on Common Crawl [45]. The word embedding is computed by representing a word as a bag of n-grams [46]. This word-internal …","url":["https://www.mdpi.com/2075-5309/13/2/377/pdf"]}
{"year":"2023","title":"Automatic Detection in Twitter of Non-Traumatic Grief due to Deaths by COVID-19. A Deep Learning Approach","authors":["J Mata-Vázquez, V Pachón-Álvarez, E Gualda… - IEEE Access, 2023"],"snippet":"Non-traumatic grief can be defined as, a complex process that includes emotional, physical, spiritual, social, and intellectual behaviors and responses through which individuals, families, and communities incorporate actual, anticipated, or perceived …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10360118.pdf"]}
{"year":"2023","title":"Automatic Extraction of Conversation Flows from Human Dialogues: Understanding Their Impact to Refine NLP Models","authors":["MF Sanches, JMC de Sá, RR de Souza, AM de Souza… - SN Computer Science, 2023"],"snippet":"… Similarly, Common Crawl [23] is a continuously updated collection of Web pages. Due to its similarity to the BrWaC, the Common Crawl is … Smith JR, Saint-Amand H, Plamada M, Koehn P, Callison-Burch C, Lopez A, Dirt cheap web-scale parallel text …","url":["https://link.springer.com/article/10.1007/s42979-023-02148-7"]}
{"year":"2023","title":"Automatic Extractive Text Summarization for Text in Nepali Language with Bidirectional Encoder Representation Transformers and K-Mean Clustering","authors":["C Pokhrel, R Adhikari"],"snippet":"… Pre-trained in over 104 diffiferent language of 2.5TB of filtered common crawl data corpus, XLMRoBERTa or XLM-R is a multilingual version of RoBERTa. It is a transformer based multilingual model which has been pretrained on large corpus of …","url":["https://www.researchgate.net/profile/Chitran-Pokhrel/publication/372221925_Automatic_Extractive_Text_Summarization_for_Text_in_Nepali_Language_with_Bidirectional_Encoder_Representation_Transformers_and_K-Mean_Clustering/links/64aa7f1dc41fb852dd60d232/Automatic-Extractive-Text-Summarization-for-Text-in-Nepali-Language-with-Bidirectional-Encoder-Representation-Transformers-and-K-Mean-Clustering.pdf"]}
{"year":"2023","title":"Automatic generation of definitions: Exploring if GPT is useful for defining words","authors":["F Eriksson - 2023"],"snippet":"When reading a text, it is common to get stuck on unfamiliar words that are difficult to understand in the local context. In these cases, we use dictionaries or similar online resources to find the general meaning of the word. However, maintaining a …","url":["https://www.diva-portal.org/smash/get/diva2:1791309/FULLTEXT01.pdf"]}
{"year":"2023","title":"Automatic Generation of German Drama Texts Using Fine Tuned GPT-2 Models","authors":["M Bangura, K Barabashova, A Karnysheva, S Semczuk… - arXiv preprint arXiv …, 2023"],"snippet":"This study is devoted to the automatic generation of German drama texts. We suggest an approach consisting of two key steps: fine-tuning a GPT-2 model (the outline model) to generate outlines of scenes based on keywords and fine-tuning a …","url":["https://arxiv.org/pdf/2301.03119"]}
{"year":"2023","title":"Automatic Genre Identification for Robust Enrichment of Massive Text Collections: Investigation of Classification Methods in the Era of Large Language Models","authors":["T Kuzman, I Mozetič, N Ljubešić - Machine Learning and Knowledge Extraction, 2023"],"snippet":"… The XLM-RoBERTa model was pre-trained on the CommonCrawl multilingual data [52], which comprise 167 billion tokens in 100 languages, out of which Slovenian is represented by 1.7 billion tokens. We use the base-sized model that …","url":["https://www.mdpi.com/2504-4990/5/3/59"]}
{"year":"2023","title":"Automatic information extraction in business document","authors":["SA Moreno Acevedo - 2023"],"snippet":"… This model was pre-trained with 2.5 TB of text data from the Common Crawl corpus [67], which includes text in 100 different languages. This extensive pre-training has allowed RoBERTa to compute text representations in multiple languages …","url":["https://bibliotecadigital.udea.edu.co/bitstream/10495/37581/1/MorenoSantiago_2023_InformationExtractionDeepLearningNaturalLanguageProcessing.pdf"]}
{"year":"2023","title":"Automatic login form leakage detection for website administrators","authors":["SW de Vries, G Acar, E Poll - 2023"],"snippet":"… We crawled a list of 30K web pages with login forms from a list composed by Roefs [56] using the the Tranco top 100K domains from a Common Crawl snapshot from November/December 2021. The Common Crawl dataset consists of a large …","url":["https://www.ru.nl/publish/pages/769526/steven_wallis_de_vries.pdf"]}
{"year":"2023","title":"Automatic Methods for Extracting Taxonomic Relationships from Texts","authors":["NV Loukachevitch - Pattern Recognition and Image Analysis, 2023"],"snippet":"… Fasttext embeddings [5], which were calculated on the Internet corpus of Common Crawl and Wikipedia, Footnote 1 turned out to be the best vector representation for predicting hypernyms. The best method in this testing was the …","url":["https://link.springer.com/article/10.1134/S1054661823030276"]}
{"year":"2023","title":"Automatic Multilingual Question Generation for Health Data Using LLMs","authors":["R Ackerman, R Balyan - International Conference on AI-generated Content, 2023"],"snippet":"Question Generation (QG) involves automatic generation of yes/no, factual and Wh-questions created from data sources such as a database, raw text or semantic representation. QG can be used in an adaptive intelligent tutoring system or a dialog system for …","url":["https://link.springer.com/chapter/10.1007/978-981-99-7587-7_1"]}
{"year":"2023","title":"Automatic pull request title generation.(2022)","authors":["T ZHANG, IC IRSAN, F THUNG, DG HAN, D LO… - 2022 IEEE International …"],"snippet":"… Unlike BART, T5 was pre-trained with the Colossal Clean Crawled Corpus (C4) dataset, which consists of 750GB of English text from the public Common Crawl web scrape. T5 was reported to achieve state-of-the-art results on many benchmarks …","url":["https://ink.library.smu.edu.sg/context/sis_research/article/8702/viewcontent/automatic.pdf"]}
{"year":"2023","title":"Automatic Scoring of Creative Problem-Solving with Large Language Models: A Comparison of Originality and Quality Ratings","authors":["S Luchini, NT Maliakkal, PV DiStefano, JD Patterson… - 2023"],"snippet":"… a collection of data from the Toronto BookCorpus (800M words), the English portion of Wikipedia (2,500M words), the CCNews English dataset (63M news articles), the OpenWebText dataset of Reddit posts, and the Stories dataset which …","url":["https://psyarxiv.com/g5qvf/download?format=pdf"]}
{"year":"2023","title":"Automatic Subjective Answer Grading Software Using Machine Learning","authors":["R Kothari, B Rangwala, K Patel - 2023 7th International Conference on Trends in …, 2023"],"snippet":"One of the major challenges during online examinations is the assessment of answers, particularly of the subjective type. Subjective answers test a student's ability to retain information and express it in natural language. While objective …","url":["https://ieeexplore.ieee.org/abstract/document/10125786/"]}
{"year":"2023","title":"Automatic Summarization of Validated Intelligence Events","authors":["TEO BECERRA, L JOHANSSON - 2023"],"snippet":"… Fortunately there exists one very large dataset, which is the Common Crawl dataset that consist of nearly a trillion words. Common Crawl is a dataset that has been obtained by crawling the web and therefore the quality of data is quite low …","url":["https://odr.chalmers.se/bitstreams/67a971d6-44e2-435c-bab7-8ed1a6899915/download"]}
{"year":"2023","title":"Automatically Assembling a Custom-Built Training Corpus for Improving the Learning of In-Domain Word/Document Embeddings","authors":["Y Blanco-Fernández, A Gil-Solla, JJ Pazos-Arias… - Informatica, 2023"],"snippet":"Embedding models turn words/documents into real-number vectors via co-occurrence data from unrelated texts. Crafting domain-specific embeddings from general corpora with limited domain vocabulary is challenging. Existing solutions retrain …","url":["https://informatica.vu.lt/journal/INFORMATICA/article/1304/text"]}
{"year":"2023","title":"Automatically Preventing, Detecting and Repairing Crucial Errors in Programs","authors":["J Zhang - 2023"],"snippet":"Today, high-impact errors in programs result in huge money losses, are notoriously expensive for programmers to repair, and affect millions of real-world users. This dissertation highlights the need to move beyond our post-mortem manual error …","url":["https://search.proquest.com/openview/7de4fd51ae4ca079578859561188cd2b/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Automating democracy: Generative AI, journalism, and the future of democracy","authors":["AR Arguedas, FM Simon - 2023"],"snippet":"Sophisticated AI systems are increasingly everywhere. In many ways, we have already been affected by the rollout of AI systems into more and more areas of life, from insurance and law to healthcare and the media – often without really noticing …","url":["https://ora.ox.ac.uk/objects/uuid:0965ad50-b55b-4591-8c3b-7be0c587d5e7/download_file?file_format=application%2Fpdf&safe_filename=Arguedas_and_Simon_2023_Automating_democracy__Generative.pdf&type_of_work=Report"]}
{"year":"2023","title":"AutoPCF: Efficient Product Carbon Footprint Accounting with Large Language Models","authors":["Z Deng, J Liu, B Luo, C Yuan, Q Yang, L Xiao, W Zhou… - arXiv preprint arXiv …, 2023"],"snippet":"… The GPT3.5 and GPT-4 training datasets include the Common Crawl dataset, the Webtext2 dataset, two internet-based book corpora, and Wikipedia7. The Common Crawl dataset, which contributes 60% of the total weight in the training mix, contains …","url":["https://arxiv.org/pdf/2308.04241"]}
{"year":"2023","title":"B\\\"{u} y\\\"{u} k dil modellerinin T\\\"{u} rk\\c {c} e verisetleri ile e\\u {g} itilmesi ve ince ayarlanmas\\i","authors":["AT Arslan - arXiv preprint arXiv:2306.03978, 2023"],"snippet":"Large language models have advanced enormously, gained vast attraction and are having a phase of intensed research. Some of the developed models and training datasets have been made open-accessible. Hence these may be further fine-tuned …","url":["https://arxiv.org/pdf/2306.03978"]}
{"year":"2023","title":"Bachelor Thesis Emergent Theory of Mind in Large Language Models","authors":["M Terentev"],"snippet":"… The emergence of transformers, known for their reduced training time compared to older long short-term memory (LSTM) models, has enabled utilizing large language datasets like the Wikipedia Corpus and Common Crawl for training …","url":["https://bnaic2023.tudelft.nl/static/media/BNAICBENELEARN_2023_paper_129.7ab7694ad3fe7122da37.pdf"]}
{"year":"2023","title":"Bachelor's Thesis Assignment","authors":["C Perone"],"snippet":"When it comes to language learning apps that allow sentence-like answers, accurately estimating the correctness score is crucial. A possible approach is to compute the semantic similarity of input sentences and predefined correct answers …","url":["https://dspace.vutbr.cz/bitstream/handle/11012/211150/final-thesis.pdf?sequence=-1"]}
{"year":"2023","title":"Back to common sense: Oxford dictionary descriptive knowledge augmentation for aspect-based sentiment analysis","authors":["W Jin, B Zhao, L Zhang, C Liu, H Yu - Information Processing & Management, 2023"],"snippet":"Aspect-based Sentiment Analysis (ABSA) is a crucial natural language understanding (NLU) research field which aims to accurately recognize reviewers’ opinions on different aspects of products and services. Despite the prominence of …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322003612"]}
{"year":"2023","title":"Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition Errors","authors":["M Kubis, P Skórzewski, M Sowański, T Ziętkiewicz - arXiv preprint arXiv:2310.16609, 2023"],"snippet":"In a spoken dialogue system, an NLU model is preceded by a speech recognition system that can deteriorate the performance of natural language understanding. This paper proposes a method for investigating the impact of speech recognition …","url":["https://arxiv.org/pdf/2310.16609"]}
{"year":"2023","title":"Back Translation for Speech-to-text Translation Without Transcripts","authors":["Q Fang, Y Feng - arXiv preprint arXiv:2305.08709, 2023"],"snippet":"… Specifically, we use europarl v78, commoncrawl9, news commentary v1210 subsets for all three languages. The source text is never used … 8http://statmt.org/wmt13/ training-parallel-europarl-v7.tgz 9http://statmt.org/wmt13/ training-parallel-commoncrawl.tgz …","url":["https://arxiv.org/pdf/2305.08709"]}
{"year":"2023","title":"Backdoor Learning on Sequence to Sequence Models","authors":["L Chen, M Cheng, H Huang - arXiv preprint arXiv:2305.02424, 2023"],"snippet":"Backdoor learning has become an emerging research area towards building a trustworthy machine learning system. While a lot of works have studied the hidden danger of backdoor attacks in image or text classification, there is a limited …","url":["https://arxiv.org/pdf/2305.02424"]}
{"year":"2023","title":"BacklinkDB: A Purpose-Built Backlink Database Management System","authors":["ML Jørgensen - 2023"],"snippet":"… Common Crawl is a non-profit organization that periodically crawls the web and publicizes data. For the experiments … Common Crawl provides data on all the indexable webpages. This data is provided in a series of warc files found in their …","url":["https://munin.uit.no/bitstream/handle/10037/28861/thesis.pdf?sequence=2&isAllowed=y"]}
{"year":"2023","title":"Bag of Words and Embedding Text Representation Methods for Medical Article Classification","authors":["P Cichosz - International Journal of Applied Mathematics and …, 2023"],"snippet":"… vectors pre-trained on the Common Crawl corpus were used.For training custom fastText vectors, the fasttext Python library10 was used (Bojanowski et al., 2020), with vector dimensionality set to 100, SG training mode, and other parameters left at …","url":["https://sciendo.com/pdf/10.34768/amcs-2023-0043"]}
{"year":"2023","title":"Baichuan 2: Open Large-scale Language Models","authors":["A Yang, B Xiao, B Wang, B Zhang, C Yin, C Lv, D Pan… - arXiv preprint arXiv …, 2023"],"snippet":"… For instance, the main data source for LLaMA is Common Crawl1, which comprises 67% of LLaMA’s pre-training data but is filtered to English content only. Other open source LLMs such as MPT (MosaicML… 1https://commoncrawl.org/ …","url":["https://arxiv.org/pdf/2309.10305"]}
{"year":"2023","title":"Balancing of tourist opinions for sentiment analysis task","authors":["AB García-Gutiérrez, PE López-Ávila… - 2023"],"snippet":"This article presents a proposal for the treatment of an unbalanced tourist database with emphasis on minority classes for its classification, in this case, one based on BERT, called BETO. This methodology originally forms part of the thesis project of …","url":["https://ceur-ws.org/Vol-3496/restmex-paper8.pdf"]}
{"year":"2023","title":"BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla","authors":["A Bhattacharjee, T Hasan, W Ahmad, R Shahriyar - Findings of the Association for …, 2023"],"snippet":"This work presents ‘BanglaNLG,’a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language. We aggregate six challenging conditional text generation tasks under the …","url":["https://aclanthology.org/2023.findings-eacl.54.pdf"]}
{"year":"2023","title":"Basic Principles of Cross-Lingual Models","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"When we start working across languages, we need to determine ways of measuring similarity of entities (such as a word, a phrase, a sentence or a link between entities) within each language and across languages. Modern approaches usually rely on …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_2"]}
{"year":"2023","title":"Behind the Scenes: Examining Efficacy of Race Classification Models with a Focus on TV","authors":["J WANG - 2023"],"snippet":"This thesis explores the use of web scraping and machine learning to enhance the predictive power of current race classification models. With the rise of online data as an important source for research, the availability of race labels typically acquired …","url":["https://www.jennywang.me/files/undergrad-thesis.pdf"]}
{"year":"2023","title":"BELT: Bootstrapping Electroencephalography-to-Language Decoding and Zero-Shot Sentiment Classification by Natural Language Supervision","authors":["J Zhou, Y Duan, YC Chang, YK Wang, CT Lin - arXiv preprint arXiv:2309.12056, 2023"],"snippet":"This paper presents BELT, a novel model and learning framework for the pivotal topic of brain-to-language translation research. The translation from noninvasive brain signals into readable natural language has the potential to promote the …","url":["https://arxiv.org/pdf/2309.12056"]}
{"year":"2023","title":"Benchmark for Evaluation of Danish Clinical Word Embeddings","authors":["MS Laursen, JS Pedersen, PJ Vinholt, RS Hansen… - Northern European Journal …, 2023"],"snippet":"In natural language processing, benchmarks are used to track progress and identify useful models. Currently, no benchmark for Danish clinical word embeddings exists. This paper describes the development of a Danish benchmark for clinical word …","url":["https://nejlt.ep.liu.se/article/download/4132/3825"]}
{"year":"2023","title":"Benchmark tasks for evaluation of language models","authors":["S Hamotskyi"],"snippet":"Language models (LMs) are an integral part of NLP, with their importance sharply increasing in recent years with the advent of large generalized LMs (such as OpenAI GPT and BERT) that reach and in some cases surpass the level of nonexpert …","url":["https://serhii.net/s/SerhiiHamotskyiBenchmarks.pdf"]}
{"year":"2023","title":"Benchmarking and Analyzing In-context Learning, Fine-tuning and Supervised Learning for Biomedical Knowledge Curation: a focused study on chemical entities of …","authors":["E Groves, M Wang, Y Abdulle, H Kunz… - arXiv preprint arXiv …, 2023"],"snippet":"Automated knowledge curation for biomedical ontologies is key to ensure that they remain comprehensive, high-quality and up-to-date. In the era of foundational language models, this study compares and analyzes three NLP paradigms for …","url":["https://arxiv.org/pdf/2312.12989"]}
{"year":"2023","title":"Benchmarking Arabic AI with Large Language Models","authors":["A Abdelali, H Mubarak, SA Chowdhury, M Hasanain… - arXiv preprint arXiv …, 2023"],"snippet":"… GPT-3 is trained mainly using a filtered version of Common Crawl dataset. The filtering is based on similarity to high-quality reference corpora. Fuzzy deduplication at document level is performed to remove redundancy and avoid contamination of …","url":["https://arxiv.org/pdf/2305.14982"]}
{"year":"2023","title":"Benchmarking Large Language Model Capabilities for Conditional Generation","authors":["J Maynez, P Agrawal, S Gehrmann - arXiv preprint arXiv:2306.16793, 2023"],"snippet":"Pre-trained large language models (PLMs) underlie most new developments in natural language processing. They have shifted the field from application-specific model pipelines to a single model that is adapted to a wide range of tasks …","url":["https://arxiv.org/pdf/2306.16793"]}
{"year":"2023","title":"Benchmarking Multilabel Topic Classification in the Kyrgyz Language","authors":["A Alekseev, SI Nikolenko, G Kabaeva - arXiv preprint arXiv:2308.15952, 2023"],"snippet":"Kyrgyz is a very underrepresented language in terms of modern natural language processing resources. In this work, we present a new public benchmark for topic classification in Kyrgyz, introducing a dataset based on collected and annotated …","url":["https://arxiv.org/pdf/2308.15952"]}
{"year":"2023","title":"Benchmarking Procedural Language Understanding for Low-Resource Languages: A Case Study on Turkish","authors":["A Uzunoğlu, GG Şahin - arXiv preprint arXiv:2309.06698, 2023"],"snippet":"Understanding procedural natural language (eg, step-by-step instructions) is a crucial step to execution and planning. However, while there are ample corpora and downstream tasks available in English, the field lacks such resources for most …","url":["https://arxiv.org/pdf/2309.06698"]}
{"year":"2023","title":"Bengali Text Classification: A New multi-class Dataset and Performance Evaluation of Machine Learning and Deep Learning Models","authors":["A Roy, K Sarkar, CK Mandal - 2023"],"snippet":"This study focuses on Bengali text classification using machine learning and deep learning techniques. Text classification is a fundamental task in natural language processing (NLP) that involves categorizing text documents into predefined …","url":["https://www.researchsquare.com/article/rs-3129157/latest.pdf"]}
{"year":"2023","title":"BERT Goes Off-Topic: Investigating the Domain Transfer Challenge using Genre Classification","authors":["D Roussinov, S Sharoff - arXiv preprint arXiv:2311.16083, 2023"],"snippet":"While performance of many text classification tasks has been recently improved due to Pre-trained Language Models (PLMs), in this paper we show that they still suffer from a performance gap when the underlying distribution of topics changes. For …","url":["https://arxiv.org/pdf/2311.16083"]}
{"year":"2023","title":"BERT-based ensemble learning for multi-aspect hate speech detection","authors":["AC Mazari, N Boudoukhani, A Djeffal - Cluster Computing, 2023"],"snippet":"… After testing FastText embedding pre-trained on Wikipedia texts and those pre-trained on Common Crawl corpus, Footnote 2 we choose to use the FastText vectors pre-trained on Common Crawl data because they provide us the best results for all the …","url":["https://link.springer.com/article/10.1007/s10586-022-03956-x"]}
{"year":"2023","title":"BERTinchamps: Cost-Effective Training of Large Language Models for Medical Tasks in French","authors":["A Fierens, S Jodogne - 2023"],"snippet":"… The OSCAR dataset is an extensive multilingual corpus acquired through language classification and filtering of the Common Crawl corpus employing the goclassy architecture. A subset of 17GB of the French part of the OSCAR dataset …","url":["http://sag.art.uniroma2.it/NL4AI/wp-content/uploads/2023/10/paper1.pdf"]}
{"year":"2023","title":"BERTuit: Understanding Spanish language in Twitter with transformers","authors":["J Huertas‐Tato, A Martín, D Camacho - Expert Systems, 2023"],"snippet":"The appearance of complex attention‐based language models such as BERT, RoBERTa or GPT‐3 has allowed to address highly complex tasks in a plethora of scenarios. However, when applied to specific domains, these models encounter …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.13404"]}
{"year":"2023","title":"Better conditioning on context for natural language processing","authors":["Q Liu - 2022"],"snippet":"… T5 introduces a new pre-training dataset, Colossal Clean Crawled Corpus by cleaning the web pages from Common Crawl. T5 also systematically compares previous methods in terms of pre-training objectives, architectures, pre-training …","url":["https://ora.ox.ac.uk/objects/uuid:abaab43c-638d-444a-b172-2a1abbb17a2d/download_file?file_format=application%2Fpdf&safe_filename=Liu_2022_Better_conditioning_on.pdf&type_of_work=Thesis"]}
{"year":"2023","title":"Better Language Support and Pragmatic System Designs for Automatic Text Summarization","authors":["D Varab - 2023"],"snippet":"… Common approaches to acquiring large amounts of text data usually involve filtering large snapshots of the internet distributed by online archives like CommonCrawl3. Such approaches provide virtually endless amounts of text data …","url":["https://en.itu.dk/-/media/EN/Research/PhD-Programme/PhD-defences/2023/PhD-Thesis-Temporary-Version-Daniel-Varab-pdf.pdf"]}
{"year":"2023","title":"Better Quality Pre-training Data and T5 Models for African Languages","authors":["A Oladipo, M Adeyemi, O Ahia, A Owodunni… - Proceedings of the 2023 …, 2023"],"snippet":"… 2019), Wikipedia and Common Crawl archive. The latter often has significant quality issues (Kreutzer et al.… noisier common crawl data. Obtaining such highquality data is tedious since it involved curating several verified sources manually. Thus …","url":["https://aclanthology.org/2023.emnlp-main.11.pdf"]}
{"year":"2023","title":"Better Translation+ Split and Generate for Multilingual RDF-to-Text (WebNLG 2023)","authors":["N Kumar, SOU Islam, O Dušek - Proceedings of the Workshop on Multimodal …, 2023"],"snippet":"This paper presents system descriptions of our submitted outputs for WebNLG Challenge 2023. We use mT5 in multi-task and multilingual settings to generate more fluent and reliable verbalizations of the given RDF triples. Furthermore, we …","url":["https://aclanthology.org/2023.mmnlg-1.8.pdf"]}
{"year":"2023","title":"Beyond Document Page Classification: Design, Datasets, and Challenges","authors":["J Van Landeghem, S Biswas, MB Blaschko, MF Moens - arXiv preprint arXiv …, 2023"],"snippet":"This paper highlights the need to bring document classification benchmarking closer to real-world applications, both in the nature of data tested ($X$: multi-channel, multi-paged, multi-industry; $Y$: class distributions and label set variety) and in classification …","url":["https://arxiv.org/pdf/2308.12896"]}
{"year":"2023","title":"Beyond Extractive: Advancing Abstractive Automatic Text Summarization in Norwegian with Transformers","authors":["JJ Navjord, JMR Korsvik - 2023"],"snippet":"Automatic summarization is a key area in natural language processing (NLP) and machine learning which attempts to generate informative summaries of articles and documents. Despite its evolution since the 1950s, research on automatically …","url":["https://nmbu.brage.unit.no/nmbu-xmlui/bitstream/handle/11250/3079868/no.nmbu:wiseflow:6839553:54763253.pdf?sequence=1"]}
{"year":"2023","title":"Beyond Fish and Bicycles: Exploring the Varieties of Online Women's Ideological Spaces","authors":["U Balci, C Ling, E De Cristofaro, M Squire, G Stringhini… - arXiv preprint arXiv …, 2023"],"snippet":"The Internet has been instrumental in connecting under-represented and vulnerable groups of people. Platforms built to foster social interaction and engagement have enabled historically disenfranchised groups to have a voice. One such vulnerable …","url":["https://arxiv.org/pdf/2303.07099"]}
{"year":"2023","title":"Beyond quantity of experience: Exploring the role of semantic consistency in Chinese character knowledge.","authors":["CY Hsieh, M Marelli, K Rastle - … of Experimental Psychology: Learning, Memory, and …, 2023"],"snippet":"Most printed Chinese words are compounds built from the combination of meaningful characters. Yet, there is a poor understanding of how individual characters contribute to the recognition of compounds. Using a megastudy of …","url":["https://psycnet.apa.org/record/2024-20164-001"]}
{"year":"2023","title":"Beyond Scale: the Diversity Coefficient as a Data Quality Metric Demonstrates LLMs are Pre-trained on Formally Diverse Data","authors":["A Lee, B Miranda, S Koyeyo"],"snippet":"… more stringent preprocessing method applied to the Common Crawl corpus for Pile-CC, which contributes to enhanced data diversity. … Since many canonical datasets already exist and are publicly available (eg Common Crawl, Wikipedia) …","url":["https://brando90.github.io/brandomiranda/professional_documents/ICML_2023_DeployGenAI_Workshop__Diversity_Coefficient___LLMs__6pg_.pdf"]}
{"year":"2023","title":"bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark","authors":["M Hardalov, P Atanasova, T Mihaylov, G Angelova… - arXiv preprint arXiv …, 2023"],"snippet":"We present bgGLUE (Bulgarian General Language Understanding Evaluation), a benchmark for evaluating language models on Natural Language Understanding (NLU) tasks in Bulgarian. Our benchmark includes NLU tasks targeting a variety of NLP …","url":["https://arxiv.org/pdf/2306.02349"]}
{"year":"2023","title":"Bhagavad Geeta Based ChatBot","authors":["A Karekar, S Limaye, A Nara, S Panchal - 2023 3rd International Conference on …, 2023"],"snippet":"… By merging data from Common Crawl and WebText, a significantly larger and more varied dataset was used to train the model. … A wide variety of data sources, including BookCorpus, Common Crawl, and Wikipedia, are used to train the GPT-3 …","url":["https://ieeexplore.ieee.org/iel7/10205372/10205375/10205716.pdf"]}
{"year":"2023","title":"Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks","authors":["KX Mei, S Fereidooni, A Caliskan - arXiv preprint arXiv:2306.05550, 2023"],"snippet":"The rapid deployment of artificial intelligence (AI) models demands a thorough investigation of biases and risks inherent in these models to understand their impact on individuals and society. This study extends the focus of bias evaluation in extant …","url":["https://arxiv.org/pdf/2306.05550"]}
{"year":"2023","title":"Bias Detection for Customer Interaction Data: A Survey on Datasets, Methods, and Tools","authors":["A Donald, A Galanopoulos, E Curry, E Muñoz, I Ullah… - IEEE Access, 2023"],"snippet":"… It is important to highlight that these embedders, though often built on Wikipedia or CommonCrawl, can be trained on a vast variety of text … on CommonCrawl, and trained on Twitter tweets. They found Twitter embeddings to produce the greatest …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10126086.pdf"]}
{"year":"2023","title":"Biases in Large Language Models: Origins, Inventory and Discussion","authors":["R Navigli, S Conia, B Ross - ACM Journal of Data and Information Quality, 2023"],"snippet":"In this paper, we introduce and discuss the pervasive issue of bias in the large language models that are currently at the core of mainstream approaches to Natural Language Processing (NLP). We first introduce data selection bias, that is, the bias …","url":["https://dl.acm.org/doi/pdf/10.1145/3597307"]}
{"year":"2023","title":"Bidirectional Contrastive Split Learning for Visual Question Answering","authors":["Y Sun, H Ochiai"],"snippet":"Visual Question Answering (VQA) based on multi-modal data facilitates real-life applications such as home robots and medical diagnoses. One significant challenge is to devise a robust decentralized learning framework for various client models …","url":["https://www.researchgate.net/profile/Yuwei-Sun-14/publication/362908270_Bidirectional_Contrastive_Split_Learning_for_Visual_Question_Answering/links/64d44adf1290c33cce7dbf0f/Bidirectional-Contrastive-Split-Learning-for-Visual-Question-Answering.pdf"]}
{"year":"2023","title":"Bilingual Terminology Alignment Using Contextualized Embeddings","authors":["I Setha, H Aliane - Proceedings of the Workshop on Computational …, 2023","S Imene, A Algeria, A Hassina - Computational Terminology in NLP and Translation …, 2023"],"snippet":"… In our work, we choose to use the Multilingual Elmo embeddings2, which was pre-trained on 20 million words data randomly sampled from the raw text released by the shared task wiki dump + common crawl, (github…","url":["https://aclanthology.org/2023.contents-1.1.pdf","https://aclanthology.org/2023.contents-1.pdf#page=7"]}
{"year":"2023","title":"Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models","authors":["X Jin, J Larson, W Yang, Z Lin - arXiv preprint arXiv:2312.09601, 2023"],"snippet":"Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature. This study delves into the potential of large language models (LLMs) for binary code comprehension. To this end, we …","url":["https://arxiv.org/pdf/2312.09601"]}
{"year":"2023","title":"Biologically Plausible Sparse Temporal Word Representations","authors":["Y Liu, W Chen, H Liu, Y Zhang, M Zhang, H Qu - IEEE Transactions on Neural …, 2023"],"snippet":"… In our experiment, we use the pretrained GloVe10(“Common Crawl” version with 2.2M vocabulary) and Word2Vec11(“Google News” version with 3.0M vocabulary) of 300 dimensions, as well as BERT-mini(256 dimensions and four layers) and BERT-base(768 …","url":["https://ieeexplore.ieee.org/abstract/document/10173851/"]}
{"year":"2023","title":"BIOptimus: Pre-training an Optimal Biomedical Language Model with Curriculum Learning for Named Entity Recognition","authors":["P Vera, M Makhlouf - arXiv preprint arXiv:2308.08625, 2023","V Pavlova, M Makhlouf - The 22nd Workshop on Biomedical Natural Language …, 2023"],"snippet":"Using language models (LMs) pre-trained in a self-supervised setting on large corpora and then fine-tuning for a downstream task has helped to deal with the problem of limited label data for supervised learning tasks such as Named Entity …","url":["https://aclanthology.org/2023.bionlp-1.31.pdf","https://arxiv.org/pdf/2308.08625"]}
{"year":"2023","title":"Bipolar Sentiment Analysis of Japanese Social Media Posts: A Semantic Similarity Based Approach","authors":["MFF Khan, N Oi, K Sakamura - 2023 Sixth International Symposium on Computer …, 2023"],"snippet":"… These vectors are trained on Common Crawl and Wikipedia using fastText with the following configuration: CBOW (continuous bag of words) with position-weights, in dimension 300, with character n-grams of length 5, a window of size 5 and 10 …","url":["https://ieeexplore.ieee.org/abstract/document/10219460/"]}
{"year":"2023","title":"BiSync: A Bilingual Editor for Synchronized Monolingual Texts","authors":["J Crego, J Xu, F Yvon - arXiv preprint arXiv:2306.00400, 2023"],"snippet":"In our globalized world, a growing number of situations arise where people are required to communicate in one or several foreign languages. In the case of written communication, users with a good command of a foreign language may find …","url":["https://arxiv.org/pdf/2306.00400"]}
{"year":"2023","title":"Bit Cipher--A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models","authors":["H Zhao, JR Williams - arXiv preprint arXiv:2311.11012, 2023"],"snippet":"While Large Language Models (LLMs) become ever more dominant, classic pre-trained word embeddings sustain their relevance through computational efficiency and nuanced linguistic interpretation. Drawing from recent studies demonstrating that the …","url":["https://arxiv.org/pdf/2311.11012"]}
{"year":"2023","title":"BiTimeBERT: Extending Pre-Trained Language Representations with Bi-Temporal Information","authors":["J Wang, A Jatowt, M Yoshikawa, Y Cai - Proceedings of the 46th International ACM …, 2023"],"snippet":"Time is an important aspect of documents and is used in a range of NLP and IR tasks. In this work, we investigate methods for incorporating temporal information during pre-training to further improve the performance on time-related tasks. Compared …","url":["https://dl.acm.org/doi/pdf/10.1145/3539618.3591686"]}
{"year":"2023","title":"BitNet: Scaling 1-bit Transformers for Large Language Models","authors":["H Wang, S Ma, L Dong, S Huang, H Wang, L Ma… - arXiv preprint arXiv …, 2023"],"snippet":"The increasing size of large language models has posed challenges for deployment and raised concerns about environmental impact due to high energy consumption. In this work, we introduce BitNet, a scalable and stable 1-bit Transformer …","url":["https://arxiv.org/pdf/2310.11453"]}
{"year":"2023","title":"Black Ostrich: Web Application Scanning with String Solvers","authors":["B Eriksson, A Stjerna, R De Masellis, P Rüemmer… - Proceedings of the 2023 …, 2023"],"snippet":"… We evaluate Black Ostrich on a set of 8,820 unique validation patterns gathered from over 21,667,978 forms from a combination of the July 2021 Common~Crawl and Tranco top 100K. For these forms and reconstructions of input elements …","url":["https://dl.acm.org/doi/abs/10.1145/3576915.3616582"]}
{"year":"2023","title":"Blacks is to Anger as Whites is to Joy? Understanding Latent Affective Bias in Large Pre-trained Neural Language Models","authors":["A Kadan, S Bhadra, MP Gangan - arXiv preprint arXiv:2301.09003, 2023"],"snippet":"… Details of training corpora used for corpus level affective bias analysis (†Giga5, ClueWeb, & Common Crawl used to pre-train XLNet are … We omit Giga5 and ClueWeb due to their unavailability as open-source corpora and Common Crawl as …","url":["https://arxiv.org/pdf/2301.09003"]}
{"year":"2023","title":"BloombergGPT: A Large Language Model for Finance","authors":["S Wu, O Irsoy, S Lu, V Dabravolski, M Dredze… - arXiv preprint arXiv …, 2023"],"snippet":"The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Large Language Models (LLMs) have been shown to be …","url":["https://arxiv.org/pdf/2303.17564"]}
{"year":"2023","title":"BongHope: An Annotated Corpus for Bengali Hope Speech Detection","authors":["T Nath, VK Singh, V Gupta - 2023"],"snippet":"… It is pretrained on 2.5TB data from CommonCrawl corpus, consisting of 100 languages. XLMRoberta tokenizer is used to tokenize the tweets, which are then fed to the ‘xlm-robertabase’ encoder to obtain the word embeddings (Conneau et al …","url":["https://www.researchsquare.com/article/rs-2819284/latest.pdf"]}
{"year":"2023","title":"Bootstrapped nDCG Estimation in the Presence of Unjudged Documents","authors":["M Fröbe, L Gienapp, M Potthast, M Hagen - … , ECIR 2023, Dublin, Ireland, April 2–6 …, 2023"],"snippet":"Retrieval studies often reuse TREC collections after the corresponding tracks have passed. Yet, a fair evaluation of new systems that retrieve documents outside the original judgment pool is not straightforward. Two common ways of dealing with …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28244-7_20"]}
{"year":"2023","title":"Bots Behaving Badly: A Products Liability Approach to Chatbot-Generated Defamation","authors":["N Brown - J. FREE SPEECH L., 2023"],"snippet":"Within two months of its launch, ChatGPT became the fastest-growing consumer application in history with more than 100 million monthly active users. 1 Created by OpenAI, a private company backed by Microsoft, ChatGPT is just one * Associate …","url":["https://www.journaloffreespeechlaw.org/brown.pdf"]}
{"year":"2023","title":"Breaking the Bias: Gender Fairness in LLMs Using Prompt Engineering and In-Context Learning","authors":["S Dwivedi, S Ghosh, S Dwivedi - 2023"],"snippet":"Large Language Models (LLMs) have been identified as carriers of societal biases, particularly in gender representation. This study introduces an innovative approach employing prompt engineering and incontext learning to rectify these biases in LLMs …","url":["https://rupkatha.com/V15/n4/v15n410.pdf"]}
{"year":"2023","title":"Bridging the Resource Gap in Cross-Lingual Embedding Space","authors":["K Bhowmik, A Ralescu - Modelling and Development of Intelligent Systems: 8th …, 2023"],"snippet":"… XLM-R uses CommonCrawl as the source of data instead of Wikipedia. The larger amount of data available through CommonCrawl has resulted in performance improvement for low-resource languages. We intend to explore these models in the future. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-27034-5_8"]}
{"year":"2023","title":"Bringing legal knowledge to the public by constructing a legal question bank using large-scale pre-trained language model","authors":["M Yuan, B Kao, TH Wu, MMK Cheung, HWH Chan… - Artificial Intelligence and …, 2023"],"snippet":"Access to legal information is fundamental to access to justice. Yet accessibility refers not only to making legal documents available to the public, but also rendering legal information comprehensible to them. A vexing problem in bringing legal …","url":["https://link.springer.com/article/10.1007/s10506-023-09367-6"]}
{"year":"2023","title":"Bringing order into the realm of Transformer-based language models for artificial intelligence and law","authors":["CM Greco, A Tagarelli - arXiv preprint arXiv:2308.05502, 2023"],"snippet":"… The training data is obtained from a filtered and cleaned version of CommonCrawl and consists of more than 2TB of data in 100 languages. Sub-word tokenization is directly applied on the raw text for all languages using a …","url":["https://arxiv.org/pdf/2308.05502"]}
{"year":"2023","title":"Broader and Deeper: A Multi-Features with Latent Relations BERT Knowledge Tracing Model","authors":["J Wang - Responsive and Sustainable Educational Futures: 18th …, 2023"],"snippet":"Knowledge tracing aims to estimate students’ knowledge state or skill mastering level over time, which is evolving into an essential task in educational technology. Traditional knowledge tracing algorithms generally use one or a few features to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=E_3TEAAAQBAJ&oi=fnd&pg=PA183&dq=commoncrawl&ots=wvqwSbXE_y&sig=vfUdeSoEi4hjXSWnN2P9caJRy0M"]}
{"year":"2023","title":"BTLM-3B-8K: 7B Parameter Performance in a 3B Parameter Model","authors":["N Dey, D Soboleva, F Al-Khateeb, B Yang, R Pathria… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce the Bittensor Language Model, called \"BTLM-3B-8K\", a new state-of-the-art 3 billion parameter open-source language model. BTLM-3B-8K was trained on 627B tokens from the SlimPajama dataset with a mixture of 2,048 and 8,192 context …","url":["https://arxiv.org/pdf/2309.11568"]}
{"year":"2023","title":"Bug Localization Model in Source Code using Ontologies","authors":["AS Da Silva, RE Garcia, LC Botega - IEEE Access, 2023"],"snippet":"… For this step, the GloVe model is pre-trained with 300dimensional vectors using the Common Crawl knowledge base [39]. As the vectors are pre-trained, the similarity is only checked for decomposed concept patterns that generate a token in …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10246255.pdf"]}
{"year":"2023","title":"Building and Using Comparable Corpora for Multilingual Natural Language Processing","authors":["S Sharoff, R Rapp, P Zweigenbaum - 2023"],"snippet":"… [25] or the use of filtered Common Crawl data [26] with the assumption that different cultures use the Web for broadly similar purposes. … For example, the multilingual BERT is trained on Wikipedias, while XLM-Roberta is trained on the …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=47zSEAAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=-pQeIA_j8S&sig=CRJNraYlCx6hEb-VzxFIFPRgM_w"]}
{"year":"2023","title":"Building Comparable Corpora","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"In a parallel corpus we know which document is a translation of what by design. If the link between documents in different languages is not known, it needs to be established. In this chapter we will discuss methods for measuring document …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_3"]}
{"year":"2023","title":"BUILDING FLEXIBLE, SCALABLE, AND MACHINE LEARNING-READY MULTIMODAL ONCOLOGY DATASETS","authors":["A Tripathi, A Waqas, K Venkatesan, Y Yilmaz, G Rasool - arXiv preprint arXiv …, 2023"],"snippet":"… For example, the rise of large general-purpose datasets like Common Crawl [6] for natural language processing (NLP) has fueled advances in language models and Artificial Intelligence (AI) assistants. One may hope that extensive, standardized …","url":["https://arxiv.org/pdf/2310.01438"]}
{"year":"2023","title":"Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models (Vision Paper)","authors":["J Rao, S Gao, G Mai, K Janowicz - 2023"],"snippet":"… For example, GPT-3 was pre-trained on a huge language corpus consisting of around 500 billion tokens from Web resources (eg, CommonCrawl, Wikipedia) and books. BLIP-2 and DINOv2 were pre-trained on 129 million images (with captions) …","url":["https://sigspatial2023.sigspatial.org/papers/paper_2437.pdf"]}
{"year":"2023","title":"Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models","authors":["J Rao, S Gao, G Mai, K Janowicz - arXiv preprint arXiv:2309.17319, 2023"],"snippet":"In recent years we have seen substantial advances in foundation models for artificial intelligence, including language, vision, and multimodal models. Recent studies have highlighted the potential of using foundation models in geospatial artificial …","url":["https://arxiv.org/pdf/2309.17319"]}
{"year":"2023","title":"Building Programmable Commons","authors":["P Terzis - 2023"],"snippet":"First, we asked ‘who shall govern the Internet?’as its decentralised and open nature promised a public sphere free from the manipulation and fragmentation of the ad-driven mass media.‘Commons’ was an omnipresent theme in this discourse. These …","url":["https://osf.io/preprints/socarxiv/yuef5/download"]}
{"year":"2023","title":"Building Web-Based Subject-Specific Corpora on the Desktop: Evaluation of Search Metrics","authors":["JP Van Belle - … Intelligence: Select Proceedings of InCITe 2022, 2023"],"snippet":"Building subject-specific or domain corpora from Web data is well-researched. However, most approaches start by using seed articles as inputs to Web crawlers and take document similarity algorithms for selection. We take a different lean …","url":["https://link.springer.com/chapter/10.1007/978-981-19-7346-8_6"]}
{"year":"2023","title":"BureauBERTo: adapting UmBERTo to the Italian bureaucratic language","authors":["S Auriemma, M Madeddu, M Miliani, A Bondielli… - 2023"],"snippet":"In this work, we introduce BureauBERTo, the first transformer-based language model adapted to the Italian Public Administration (PA) and technical-bureaucratic domains. We further pre-trained the general-purpose Italian model UmBERTo on a …","url":["https://colinglab.fileli.unipi.it/wp-content/uploads/2023/04/Ital_IA_2023_BureauBERTo.pdf"]}
{"year":"2023","title":"calamanCy: A Tagalog Natural Language Processing Toolkit","authors":["LJV Miranda - arXiv preprint arXiv:2311.07171, 2023"],"snippet":"We introduce calamanCy, an open-source toolkit for constructing natural language processing (NLP) pipelines for Tagalog. It is built on top of spaCy, enabling easy experimentation and integration with other frameworks. calamanCy addresses the …","url":["https://arxiv.org/pdf/2311.07171"]}
{"year":"2023","title":"Calibrating a Transformer-Based Model's Confidence on Community-Engaged Research Studies: Decision Support Evaluation Study","authors":["B Ferrell, SE Raskin, EB Zimmerman - JMIR Formative Research, 2023"],"snippet":"… This type of model was made for cross-lingual transfer learning tasks and is trained on >2 terabytes of the Common Crawl corpus. It differs from BERT in terms of its tokenization and masking pattern, thus making it an interesting model with which …","url":["https://formative.jmir.org/2023/1/e41516/"]}
{"year":"2023","title":"CamPros at CASE 2022 Task 1: Transformer-based Multilingual Protest News Detection","authors":["N Kumari, M Anand, T Mohan, P Kumaraguru… - Proceedings of the 5th …, 2022"],"snippet":"Socio-political protests often lead to grave consequences when they occur. The early detection of such protests is very important for taking early precautionary measures. However, the main shortcoming of protest event detection is the scarcity …","url":["https://aclanthology.org/2022.case-1.24.pdf"]}
{"year":"2023","title":"Can ChatGPT Replace Traditional KBQA Models? An In-Depth Analysis of the Question Answering Performance of the GPT LLM Family","authors":["Y Tan, D Min, Y Li, W Li, N Hu, Y Chen, G Qi - International Semantic Web …, 2023"],"snippet":"ChatGPT is a powerful large language model (LLM) that covers knowledge resources such as Wikipedia and supports natural language question answering using its own knowledge. Therefore, there is growing interest in exploring whether …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47240-4_19"]}
{"year":"2023","title":"Can Large Language Models Capture Dissenting Human Voices?","authors":["N Lee, N An, J Thorne - Proceedings of the 2023 Conference on Empirical …, 2023"],"snippet":"Large language models (LLMs) have shown impressive achievements in solving a broad range of tasks. Augmented by instruction fine-tuning, LLMs have also been shown to generalize in zero-shot settings as well. However, whether LLMs closely …","url":["https://aclanthology.org/2023.emnlp-main.278.pdf"]}
{"year":"2023","title":"Can Large Language Models Generate Outpatient Clinic Letters at First Consultation That Incorporate Complication Profiles From UK and USA Aesthetic Plastic …","authors":["RHR Roberts, SR Ali, TD Dobbs, IS Whitaker - Aesthetic Surgery Journal Open …, 2023","TD Dobbs, IS Whitaker, MA Cantab - Aesthetic Surgery Journal, 2024"],"snippet":"Background The importance of written communication between clinicians and patients, especially in the wake of the Supreme Court case of Montgomery vs Lanarkshire, has led to a shift towards patient-centric care in the UK. This study …","url":["https://academic.oup.com/asjopenforum/advance-article/doi/10.1093/asjof/ojad109/7459516","https://www.researchgate.net/profile/Rich-Roberts-2/publication/376374844_Can_Large_Language_Models_Generate_Outpatient_Clinic_Letters_at_First_Consultation_That_Incorporate_Complication_Profiles_From_UK_and_USA_Aesthetic_Plastic_Surgery_Associations/links/659c25f96f6e450f19d775da/Can-Large-Language-Models-Generate-Outpatient-Clinic-Letters-at-First-Consultation-That-Incorporate-Complication-Profiles-From-UK-and-USA-Aesthetic-Plastic-Surgery-Associations.pdf"]}
{"year":"2023","title":"Can Peanuts Fall in Love with Distributional Semantics?","authors":["JA Michaelov, S Coulson, BK Bergen - arXiv preprint arXiv:2301.08731, 2023"],"snippet":"The context in which a sentence appears can drastically alter our expectations about upcoming words - for example, following a short story involving an anthropomorphic peanut, experimental participants are more likely to expect the sentence 'the peanut …","url":["https://arxiv.org/pdf/2301.08731"]}
{"year":"2023","title":"Can we Debunk Disinformation by Leveraging SpeakerCredibility and Perplexity Measures?","authors":["AFUR Khilji, A Sachan, D Lachi, AV Singh, TD Singh - 2023"],"snippet":"In the present age, őghting disinformation is the main concern after pandemic. The exponential growth of fake news and its role in deteriorating general public trust and democratic standards certainly calls for counter-combat approaches. The prediction …","url":["https://www.researchsquare.com/article/rs-2764182/latest.pdf"]}
{"year":"2023","title":"cantnlp@ LT-EDI-2023: Homophobia/Transphobia Detection in Social Media Comments using Spatio-Temporally Retrained Language Models","authors":["S Wong, M Durward, B Adams, J Dunn - Proceedings of the Third Workshop on …, 2023"],"snippet":"This paper describes our multiclass classification system developed as part of the LT-EDI@ RANLP-2023 shared task. We used a BERT-based language model to detect homophobic and transphobic content in social media comments across five …","url":["https://aclanthology.org/2023.ltedi-1.15.pdf"]}
{"year":"2023","title":"cantnlp@ LT-EDI@ RANLP-2023: Homophobia/Transphobia Detection in Social Media Comments using Spatio-Temporally Retrained Language Models","authors":["SGJ Wong, M Durward, B Adams, J Dunn - arXiv preprint arXiv:2308.10370, 2023"],"snippet":"This paper describes our multiclass classification system developed as part of the LTEDI@RANLP-2023 shared task. We used a BERT-based language model to detect homophobic and transphobic content in social media comments across five …","url":["https://arxiv.org/pdf/2308.10370"]}
{"year":"2023","title":"CAPS: A Practical Partition Index for Filtered Similarity Search","authors":["G Gupta, J Yi, B Coleman, C Luo, V Lakshman… - arXiv preprint arXiv …, 2023"],"snippet":"With the surging popularity of approximate near-neighbor search (ANNS), driven by advances in neural representation learning, the ability to serve queries accompanied by a set of constraints has become an area of intense interest. While …","url":["https://arxiv.org/pdf/2308.15014"]}
{"year":"2023","title":"Cataloging of Internet resources","authors":["TV Eremenko"],"snippet":"… Common crawl en A large resource that contains a lot of information of a high scientific level, covering not only human biology, but also a number of issues of general biology (in particular, molecular and cellular biology). Relatively …","url":["https://technerium.ru/en/katalogizaciya-resursov-internet-internet-katalogizaciya/"]}
{"year":"2023","title":"CCpdf: Building a High Quality Corpus for Visually Rich Documents from Web Crawl Data","authors":["M Turski, T Stanisławek, K Kaczmarek, P Dyda… - arXiv preprint arXiv …, 2023"],"snippet":"… The spike for the year 2021 was probably caused by the use of the Common Crawl dump from May 2022. We assume that crawlers from Common Crawl usually tend to find files that are a few months old, which often means that they are from the …","url":["https://arxiv.org/pdf/2304.14953"]}
{"year":"2023","title":"CEIA-NLP at CASE 2022 Task 1: Protest News Detection for Portuguese","authors":["D Fernandes, A Junior, G Marques, A Soares… - Proceedings of the 5th …, 2022"],"snippet":"This paper summarizes our work on the document classification subtask of Multilingual protest news detection of the CASE@ ACL-IJCNLP 2022 workshok. In this context, we investigate the performance of monolingual and multilingual …","url":["https://aclanthology.org/2022.case-1.26.pdf"]}
{"year":"2023","title":"Center for Artificial Intelligence Challenge on Conversational AI Correctness","authors":["M Kubis, P Skórzewski, M Sowanski, T Zietkiewicz - 2023"],"snippet":"This paper describes a challenge on Conversational AI correctness with the goal to develop Natural Language Understanding models that are robust against speech recognition errors. The data for the competition consist of natural language …","url":["https://annals-csis.org/proceedings/2023/pliks/6058.pdf"]}
{"year":"2023","title":"Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster","authors":["N Dey, G Gosal, H Khachane, W Marshall, R Pathria… - arXiv preprint arXiv …, 2023"],"snippet":"We study recent research advances that improve large language models through efficient pre-training and scaling, and open datasets and tools. We combine these advances to introduce Cerebras-GPT, a family of open compute-optimal language …","url":["https://arxiv.org/pdf/2304.03208"]}
{"year":"2023","title":"CFDA & CLIP at TREC 2022 NeuCLIR Track","authors":["JH Ju, WC Chen, HT Chang, CW Lin, MF Tsai…"],"snippet":"In this notebook paper, we report our methods for NeuCLIR track in TREC 2022. We adopt the common multistage pipeline for cross-language information retrieval task (CLIR). The pipeline includes the machine translation, sparse passage retrieval and the …","url":["https://dylanjoo.github.io/files/trec.neuclir.2022.paper.pdf"]}
{"year":"2023","title":"Challenges and Applications of Large Language Models","authors":["J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu… - arXiv preprint arXiv …, 2023"],"snippet":"Large Language Models (LLMs) went from non-existent to ubiquitous in the machine learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify the remaining challenges and already fruitful application areas. In this paper …","url":["https://arxiv.org/pdf/2307.10169"]}
{"year":"2023","title":"Challenges of Large Language Models for Mental Health Counseling","authors":["NC Chung, G Dyer, L Brocki - arXiv preprint arXiv:2311.13857, 2023"],"snippet":"… One of the largest data sources for LLMs is the CommonCrawl [19, 20] which contains 390 TB with more than 3.1 billion pages of websites. 46% of documents are in English followed by German and Russian. This focus on sources emanating from …","url":["https://arxiv.org/pdf/2311.13857"]}
{"year":"2023","title":"Challenging News Media Narratives on Refugees","authors":["RE Trulsson, V Sundelin"],"snippet":"… The model used for this project is the GloVe embeddings model that has been trained on the Common Crawl dataset. It consists of a vast collection of web pages and related metadata. (Common Crawl Foundation, nd). Training GloVe …","url":["https://research.cbs.dk/files/98734167/1646774_Challenging_News_Media_Narratives_on_Refugees.pdf"]}
{"year":"2023","title":"Challenging specialized transformers on zero-shot classification","authors":["S Auriemma, M Madeddu, M Miliani, A Bondielli… - 2023"],"snippet":"… We may suppose that this is due to the fact that UmBERTo was trained on Common-Crawl, which also contains legal and administrative texts in its Italian section. Very high results are obtained by UmBERTo for PER entities, reaching …","url":["https://clic2023.ilc.cnr.it/wp-content/uploads/2023/11/paper6.pdf"]}
{"year":"2023","title":"Change is Hard: A Closer Look at Subpopulation Shift","authors":["Y Yang, H Zhang, D Katabi, M Ghassemi - arXiv preprint arXiv:2302.12254, 2023"],"snippet":"Machine learning models often perform poorly on subgroups that are underrepresented in the training data. Yet, little is understood on the variation in mechanisms that cause subpopulation shifts, and how algorithms generalize across …","url":["https://arxiv.org/pdf/2302.12254"]}
{"year":"2023","title":"ChaPat at SemEval-2023 Task 9: Text Intimacy Analysis using Ensembles of Multilingual Transformers","authors":["T Chavan, V Patwardhan - Proceedings of the The 17th International Workshop on …, 2023"],"snippet":"Intimacy estimation of a given text has recently gained importance due to the increase in direct interaction of NLP systems with humans. Intimacy is an important aspect of natural language and has a substantial impact on our everyday …","url":["https://aclanthology.org/2023.semeval-1.181.pdf"]}
{"year":"2023","title":"Character, Word, or Both? Revisiting the Segmentation Granularity for Chinese Pre-trained Language Models","authors":["X Liang, Z Zhou, H Huang, S Wu, T Xiao, M Yang, Z Li… - arXiv preprint arXiv …, 2023"],"snippet":"Pretrained language models (PLMs) have shown marvelous improvements across various NLP tasks. Most Chinese PLMs simply treat an input text as a sequence of characters, and completely ignore word information. Although Whole Word Masking …","url":["https://arxiv.org/pdf/2303.10893"]}
{"year":"2023","title":"Characterizing Bias in Word Embeddings Towards Analyzing Gender Associations in Philippine Texts","authors":["LCL Gamboa, MRJE Estuar - 2023 IEEE World Conference on Applied Intelligence …, 2023"],"snippet":"The steady increase in computational gender bias research has been mostly done on languages for which reliable NLP packages are readily available—such as English, Chinese, and Spanish. This study expands on this area of research by …","url":["https://ieeexplore.ieee.org/abstract/document/10263949/"]}
{"year":"2023","title":"Chat GPT: A magical tool or the end of traditional language learning and teaching approach","authors":["HDA Chi - KHOA HỌC VÀ CÔNG NGHỆ GIAO THÔNG VẬN TẢI"],"snippet":"… GPT-3 was trained on hundreds of billions of words around 45 terabytes of text and its dataset mostly comes from Common Crawl, WebText2, and Wikipedia [7],[4]. Furthermore, GPT3has more than 175 billion machine learning parameters that are …","url":["https://www.researchgate.net/profile/Hiep-Nguyen-36/publication/376355267_Opportunities_and_Chellenges_for_exporting_agricultural_food_to_Middle_East_market_-_From_World_Logistics_Passport'_perspectives/links/6573e2666610947889aef1c9/Opportunities-and-Chellenges-for-exporting-agricultural-food-to-Middle-East-market-From-World-Logistics-Passport-perspectives.pdf#page=295"]}
{"year":"2023","title":"Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendations","authors":["A Qammar, H Wang, J Ding, A Naouri, M Daneshmand… - arXiv preprint arXiv …, 2023"],"snippet":"Chatbots shifted from rule-based to artificial intelligence techniques and gained traction in medicine, shopping, customer services, food delivery, education, and research. OpenAI developed ChatGPT blizzard on the Internet as it crossed one …","url":["https://arxiv.org/pdf/2306.09255"]}
{"year":"2023","title":"ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge","authors":["Y Li, Z Li, K Zhang, R Dan, S Jiang, Y Zhang - Cureus, 2023"],"snippet":"Objective The primary aim of this research was to address the limitations observed in the medical knowledge of prevalent large language models (LLMs) such as ChatGPT, by creating a specialized language model with enhanced accuracy in …","url":["https://www.cureus.com/articles/152858-chatdoctor-a-medical-chat-model-fine-tuned-on-a-large-language-model-meta-ai-llama-using-medical-domain-knowledge.pdf"]}
{"year":"2023","title":"ChatDoctor: A Medical Chat Model Fine-tuned on LLaMA Model using Medical Domain Knowledge","authors":["L Yunxiang, L Zihan, Z Kai, D Ruilong, Z You - arXiv preprint arXiv:2303.14070, 2023"],"snippet":"Recent large language models (LLMs) in the general domain, such as ChatGPT, have shown remarkable success in following instructions and producing human-like responses. However, such language models have not been learned individually and …","url":["https://arxiv.org/pdf/2303.14070"]}
{"year":"2023","title":"ChatGPT 101: Introduction to Generative AI","authors":["JY Kung - 2023"],"snippet":"The slides accompany a ChatGPT workshop that is intended for university students to learn more about generative AI and in the context of ChatGPT. This work is licensed under a Creative Commons license so that others may share and adapt the …","url":["https://era.library.ualberta.ca/items/9575d988-27c4-4387-ae5a-c48feca16f07/download/6fe1a0b7-5d1f-4c6a-9c46-3a7d01cea630"]}
{"year":"2023","title":"ChatGPT and Big Data: Enhancing Text-to-Speech Conversion","authors":["HA Dida, DSK Chakravarthy, F Rabbi - Mesopotamian Journal of Big Data, 2023"],"snippet":"Text-to-speech (TTS) conversion is a crucial technology for various applications, including accessibility, education, and entertainment. With the rapid growth of big data, TTS conversion systems face new challenges in terms of data size and diversity …","url":["https://mesopotamian.press/journals/index.php/bigdata/article/download/47/64"]}
{"year":"2023","title":"ChatGPT and Environmental Research","authors":["JJ Zhu, J Jiang, M Yang, ZJ Ren - Environmental Science & Technology, 2023"],"snippet":"ChatGPT, the latest text-based artificial intelligence (AI) tool, has quickly gained popularity and is poised to revolutionize various aspects of our lives, including education and research. With its advanced natural language processing (NLP) …","url":["https://pubs.acs.org/doi/full/10.1021/acs.est.3c01818"]}
{"year":"2023","title":"ChatGPT backend: A comprehensive analysis","authors":["A Belgacem, A BRADAI, K Beghdad-Bey - 2023 International Symposium on …, 2023"],"snippet":"… Some of the significant datasets used in training different versions of ChatGPT models include booksCorpus, common crawl, english … Some of the most popular types of such datasets are omageNet, common crawl, openstreetMap, million song …","url":["https://ieeexplore.ieee.org/abstract/document/10323792/"]}
{"year":"2023","title":"ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning","authors":["VD Lai, NT Ngo, APB Veyseh, H Man, F Dernoncourt… - arXiv preprint arXiv …, 2023"],"snippet":"… Regarding the classification of high-, medium-, low-, and extremely low-resource languages, our work currently relies on data ratios for the languages in the CommonCrawl corpus. According to our experiments, it is interesting that the performance …","url":["https://arxiv.org/pdf/2304.05613"]}
{"year":"2023","title":"ChatGPT in Education","authors":["D Psarras, I Valsamara, I Pitas"],"snippet":"• ChatGPT is a Large Language Model (LLM) that is finetuned from a Generative Pre-Trained Transformer-3.5 (GPT-3.5) series LLM, produced by OpenAI.• An LLM is a Deep Neural Network (DNN) trained to generate text similar to human language.• The fine-tuning …","url":["https://icarus.csd.auth.gr/wp-content/uploads/2023/02/ChatGPT-in-Education-v1.0.pdf"]}
{"year":"2023","title":"ChatGPT Makes Medicine Easy to Swallow: An Exploratory Case Study on Simplified Radiology Reports","authors":["K Jeblick, B Schachtner, J Dexl, A Mittermeier… - arXiv preprint arXiv …, 2022"],"snippet":"The release of ChatGPT, a language model capable of generating text that appears human-like and authentic, has gained significant attention beyond the research community. We expect that the convincing performance of ChatGPT incentivizes …","url":["https://arxiv.org/pdf/2212.14882"]}
{"year":"2023","title":"ChatGPT Needs SPADE (Sustainability, PrivAcy, Digital divide, and Ethics) Evaluation: A Review.","authors":["K Dev"],"snippet":"ChatGPT is another large language model (LLM) inline but due to its performance and ability to converse effectively, it has gained a huge popularity amongst research as well as industrial community. Recently, many studies have been published to …","url":["https://www.researchgate.net/profile/Sunder-Khowaja/publication/369901757_ChatGPT_Needs_SPADE_Sustainability_PrivAcy_Digital_divide_and_Ethics_Evaluation_A_Review/links/64328faead9b6d17dc46ae1f/ChatGPT-Needs-SPADE-Sustainability-PrivAcy-Digital-divide-and-Ethics-Evaluation-A-Review.pdf"]}
{"year":"2023","title":"ChatGPT Prompting Cannot Estimate Predictive Uncertainty in High-Resource Languages","authors":["M Pelucchi, M Valdenegro-Toro - arXiv preprint arXiv:2311.06427, 2023"],"snippet":"… in web content [19] or in the Common Crawl dataset [7] can give an estimation of the distribution of language in ChatGPT’s training data. Table 1 gives an overview of the percentage of web content and of the Common Crawl dataset in different …","url":["https://arxiv.org/pdf/2311.06427"]}
{"year":"2023","title":"ChatGPT versus the neurosurgical written boards: a comparative analysis of artificial intelligence/machine learning performance on neurosurgical board–style …","authors":["BS Hopkins, VN Nguyen, J Dallas, P Texakalidis… - Journal of Neurosurgery, 2023"],"snippet":"… These same models are further trained on extremely large databases of books, articles, websites, and more through common crawl data extraction, a method of broadly web scraping the internet for incredibly wide variety and depth of available …","url":["https://thejns.org/view/journals/j-neurosurg/aop/article-10.3171-2023.2.JNS23419/article-10.3171-2023.2.JNS23419.xml"]}
{"year":"2023","title":"ChatGPT versus Traditional Question Answering for Knowledge Graphs: Current Status and Future Directions Towards Knowledge Graph Chatbots","authors":["R Omar, O Mangukiya, P Kalnis, E Mansour - arXiv preprint arXiv:2302.06466, 2023"],"snippet":"… It was trained on massive datasets from different open-access scientific sources, such as papers and filtered common crawl. Its training datasets also included some general knowledge, such as Wikipedia. Traditional QASs for KGs divide the question-answering …","url":["https://arxiv.org/pdf/2302.06466"]}
{"year":"2023","title":"ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?","authors":["H Chen, F Jiao, X Li, C Qin, M Ravaut, R Zhao, C Xiong… - arXiv preprint arXiv …, 2023"],"snippet":"Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce. Through instruction-tuning a large language model (LLM) with supervised fine-tuning and reinforcement learning from …","url":["https://arxiv.org/pdf/2311.16989"]}
{"year":"2023","title":"ChatGPT, Let Us Chat Sign Language: Experiments, Architectural Elements, Challenges and Research Directions","authors":["N Shahin, L Ismail - … International Symposium on Networks, Computers and …, 2023"],"snippet":"ChatGPT is a language model based on Generative AI. Existing research work on ChatGPT focused on its use in various domains. However, its potential for Sign Language Translation (SLT) is yet to be explored. This paper addresses this void …","url":["https://ieeexplore.ieee.org/abstract/document/10323974/"]}
{"year":"2023","title":"ChatGPT/AIGC and Educational Innovation: Opportunities, Challenges, and the Future","authors":["Y Zhu, F Yang - Journal of East China Normal University (Educational …, 2023"],"snippet":"… 尤其到 GPT-3 时,数 据已经空前庞大,综合了 Common Crawl(约占 60%),WebText2(约 占 21%),Books1(约占 8%), Books2(约占 8%),Wikipedia(约占 3%)等不同来源的资料,囊括 了基于 3 000 亿单词语料的 1 750 亿参 数量和 45TB 数据量.在海量的数据支撑之下,ChatGPT …","url":["https://xbjk.ecnu.edu.cn/EN/article/downloadArticleFile.do?attachType=PDF&id=10962"]}
{"year":"2023","title":"ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope","authors":["PP Ray - Internet of Things and Cyber-Physical Systems, 2023"],"snippet":"… C4 Corpus: T5 is pretrained on a large-scale dataset called Colossal Clean Crawled Corpus (C4), which is a cleaned and deduplicated version of the Common Crawl dataset. This large-scale pretraining helps T5 learn general language …","url":["https://www.sciencedirect.com/science/article/pii/S266734522300024X"]}
{"year":"2023","title":"ChatGPT: promise and challenges for deployment in low-and middle-income countries","authors":["X Wang, HM Sanders, Y Liu, K Seang, BX Tran… - The Lancet Regional Health …, 2023"],"snippet":"In lowand middle-income countries (LMICs), the fields of medicine and public health grapple with numerous challenges that continue to hinder patients' access to healthcare services. ChatGPT, a publicly accessible chatbot, has emerged as a …","url":["https://www.thelancet.com/journals/lanwpc/article/PIIS2666-6065(23)00223-7/fulltext"]}
{"year":"2023","title":"ChatGPT: towards an AI subjectivity","authors":["K D'Amato"],"snippet":"Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented …","url":["https://philarchive.org/archive/DAMCTA"]}
{"year":"2023","title":"ChatGPT–the quintessence of neural networks","authors":["DS Andronchik, NS Denisyuk - 2023"],"snippet":"Andronchik, DS ChatGPT–the quintessence of neural networks/DS Andronchik, NS Denisyuk; sci. sup. IY Vanik//Знание иностранного языка как основной фактор для работы в инновационных условиях [Электронный ресурс]: сборник …","url":["https://rep.bntu.by/bitstream/handle/data/128956/44-45.pdf?sequence=1"]}
{"year":"2023","title":"ChatPLUG: Open-Domain Generative Dialogue System with Internet-Augmented Instruction Tuning for Digital Human","authors":["J Tian, H Chen, G Xu, M Yan, X Gao, J Zhang, C Li… - arXiv preprint arXiv …, 2023"],"snippet":"In this paper, we present ChatPLUG, a Chinese open-domain dialogue system for digital human applications that instruction finetunes on a wide range of dialogue tasks in a unified internet-augmented format. Different from other open-domain …","url":["https://arxiv.org/pdf/2304.07849"]}
{"year":"2023","title":"Check for Adaptation of Enterprise Modeling Methods for Large Language Models Balbir S. Barn¹, Souvik Barat2, and Kurt Sandkuhl³ (~) 2","authors":["BS Barn¹, S Barat, K Sandkuhl - The Practice of Enterprise Modeling: 16th IFIP Working …"],"snippet":"… GPT-3 uses 175 billion parameters and is trained on data from the Common Crawl data set1 comprising nearly a trillion words. The development in large language models and their evolution has been widely documented and the reader is …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=x33lEAAAQBAJ&oi=fnd&pg=PA3&dq=commoncrawl&ots=yZjIB74VvW&sig=iXBwedEgwfVyM9NjjqVO5uU0Gm0"]}
{"year":"2023","title":"Check for Matching Production and Test Files: A Comparison of Filename and Statement-Based Approaches Gerald Kipruto Kirui and Stephen Phillip Levitt ()℗","authors":["GK Kirui - South African Institute of Computer Scientists and …"],"snippet":"Accurate matching of test and production files plays a critical role in the analysis and evaluation of Test-Driven Development (TDD). However, current approaches often yield unsatisfactory results due to their reliance on filename-based matching. The …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=5RrOEAAAQBAJ&oi=fnd&pg=PA3&dq=commoncrawl&ots=AWT_pDhy-Y&sig=ogepcXvqhd82yay_4CyuSQijtEk"]}
{"year":"2023","title":"Check for updates","authors":["D Chernyshev¹, B Dobrov - Analysis of Images, Social Networks and Texts: 11th …","F de Wet¹, R Eiselen, E Schillack¹, M Puttkammer - … South Africa, December 4–8, 2023 …, 2023"],"snippet":"… The Common Crawl (CC) data set is likely the largest text data set currently available consisting of (bi-) monthly crawls of the web, and is … Part of the common crawl collection process is language identification to categorise the predominant …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=S2D8EAAAQBAJ&oi=fnd&pg=PA64&dq=commoncrawl&ots=Tcmrm2XA42&sig=YOsm8gJWgUfejEUxVK6gVlcs67U","https://books.google.de/books?hl=en&lr=lang_en&id=qGrmEAAAQBAJ&oi=fnd&pg=PA120&dq=commoncrawl&ots=En5ltGlbKd&sig=bvZREoMhuoYUncoNIhO0br41Nlc"]}
{"year":"2023","title":"Check for","authors":["F Deimling, M Fazzolari - Data and Applications Security and Privacy XXXVII …, 2023"],"snippet":"… These models are trained with data from Wikipedia and Common Crawl and evaluated on word analogy tasks. For a triplet of words A: B:: C, the goal is to guess D. For example, for the triplet Paris France:: Berlin:?, the answer would be Germany. …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=jfzKEAAAQBAJ&oi=fnd&pg=PA367&dq=commoncrawl&ots=TvPgHbh8hv&sig=1OVZEq3e_0e-fcN13D2wSBbvDY4"]}
{"year":"2023","title":"CheckIT!: A Corpus of Expert Fact-checked Claims for Italian","authors":["J Gili, L Passaro, T Caselli - 2023"],"snippet":"This paper introduces CheckIT!, a resource of expert fact-checked claims, filling a gap for the development of fact-checking pipelines in Italian. We further investigate the use of three state-of-the-art generative text models to create variations of claims …","url":["https://clic2023.ilc.cnr.it/wp-content/uploads/2023/11/paper28.pdf"]}
{"year":"2023","title":"ChessGPT: Bridging Policy Learning and Language Modeling","authors":["X Feng, Y Luo, Z Wang, H Tang, M Yang, K Shao… - arXiv preprint arXiv …, 2023"],"snippet":"… Existing dataset Numerous existing datasets comprise general internet crawl data from platforms like CommonCrawl or Wikipedia. We establish a filtering pipeline to extract only chess-related language corpus from pre-existing language corpus …","url":["https://arxiv.org/pdf/2306.09200"]}
{"year":"2023","title":"Chinesewebtext: Large-scale high-quality Chinese web text extracted with effective evaluation model","authors":["J Chen, P Jian, T Xi, Y Yi, C Ding, Q Du, G Zhu, C Zong… - arXiv preprint arXiv …, 2023"],"snippet":"… Training Data Composition While the evaluation in our current experiment targets CommonCrawl data, we believe the positive training samples … Since CommonCrawl data has a relatively high noise level overall, we directly sampled …","url":["https://arxiv.org/pdf/2311.01149"]}
{"year":"2023","title":"CHORUS: Foundation Models for Unified Data Discovery and Exploration","authors":["M Kayali, A Lykov, I Fountalis, N Vasiloglou, D Olteanu… - arXiv preprint arXiv …, 2023"],"snippet":"We explore the application of foundation models to data discovery and exploration tasks. Foundation models are large language models (LLMs) that show promising performance on a range of diverse tasks unrelated to their training. We show that …","url":["https://arxiv.org/pdf/2306.09610"]}
{"year":"2023","title":"Chuweb21D: A Deduped English Document Collection for Web Search Tasks","authors":["Z Chu, T Sakai, Q Ai, Y Liu - 2023"],"snippet":"… The Chuweb21 collection is constructed based on the 2021-17 (April, 2021) block of the Common Crawl dataset 3. We choose Common Crawl as the cornerstone corpus mainly due to its timeliness and accessibility. As a non-profit project …","url":["http://www.thuir.cn/group/~YQLiu/publications/SIGIR-AP2023Chu.pdf"]}
{"year":"2023","title":"Cicognini at ACTI: Analysis of techniques for conspiracies individuation in Italian","authors":["G Cignoni, A Bucci - 2023"],"snippet":"This report illustrates methods and results for solving SubtaskA (conspiracy detection) and SubtaskB (conspiracy topic classification) of EVALITA 2023 ACTI challenge. We employed different transformer-based models and an original method based on tf-idf …","url":["https://ceur-ws.org/Vol-3473/paper40.pdf"]}
{"year":"2023","title":"CiT: Curation in Training for Effective Vision-Language Data","authors":["H Xu, S Xie, PY Huang, L Yu, R Howes, G Ghosh… - arXiv preprint arXiv …, 2023"],"snippet":"Large vision-language models are generally applicable to many downstream tasks, but come at an exorbitant training cost that only large institutions can afford. This paper trades generality for efficiency and presents Curation in Training (CiT), a …","url":["https://arxiv.org/pdf/2301.02241"]}
{"year":"2023","title":"CKingCoder at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis","authors":["B Harish, D Naveen, P Balasubramanian, S Aarthi - Proceedings of the The 17th …, 2023"],"snippet":"The SemEval 2023 Task 9 Multilingual Tweet Intimacy Analysis, is a shared task for analysing the intimacy in the tweets posted on Twitter. The dataset was provided by Pei and Jurgens, who are part of the task organisers, for this task consists of tweets …","url":["https://aclanthology.org/2023.semeval-1.276.pdf"]}
{"year":"2023","title":"CLAD-ST: Contrastive Learning with Adversarial Data for Robust Speech Translation","authors":["SR Indurthi, S Chollampatt, R Agrawal, M Turchi - Proceedings of the 2023 …, 2023"],"snippet":"The cascaded approach continues to be the most popular choice for speech translation (ST). This approach consists of an automatic speech recognition (ASR) model and a machine translation (MT) model that are used in a pipeline to translate …","url":["https://aclanthology.org/2023.emnlp-main.560.pdf"]}
{"year":"2023","title":"CLAMP: Contrastive LAnguage Model Prompt-tuning","authors":["P Teterwak, X Sun, BA Plummer, K Saenko, SN Lim - arXiv preprint arXiv:2312.01629, 2023"],"snippet":"Large language models (LLMs) have emerged as powerful general-purpose interfaces for many machine learning problems. Recent work has adapted LLMs to generative visual tasks like image captioning, visual question answering, and visual …","url":["https://arxiv.org/pdf/2312.01629"]}
{"year":"2023","title":"Clarifying the Dialogue-Level Performance of GPT-3.5 and GPT-4 in Task-Oriented and Non-Task-Oriented Dialogue Systems","authors":["S Iizuka, S Mochizuki, A Ohashi, S Yamashita, A Guo… - 2023"],"snippet":"… It has been pre-trained on the Wikipedia and Common Crawl datasets. In this experiment, we utilized a model with 3B parameters4, which is more than the Japanese-dialog-transformers model. We built the system by LoRA-tuning (Hu et al …","url":["https://ai-hri.github.io/2023/papers/FSS-23_paper_632_cr.pdf"]}
{"year":"2023","title":"Class Cardinality Comparison as a Fermi Problem","authors":["S Ghosh, S Razniewski, G Weikum - arXiv preprint arXiv:2303.04532, 2023"],"snippet":"… The common crawl [3] is another massive dataset of textual information, almost 50 times greater than Wikipedia (around 5.6 TB) and the BookCorpus (6 GB). It requires significant processing before it can be used for pre-training large LMs [18]. A case …","url":["https://arxiv.org/pdf/2303.04532"]}
{"year":"2023","title":"ClassBases at CASE-2022 Multilingual Protest Event Detection Tasks: Multilingual Protest News Detection and Automatically Replicating Manually Created Event …","authors":["P Wiriyathammabhum - arXiv preprint arXiv:2301.06617, 2023"],"snippet":"In this report, we describe our ClassBases submissions to a shared task on multilingual protest event detection. For the multilingual protest news detection, we participated in subtask-1, subtask-2, and subtask-4, which are document …","url":["https://arxiv.org/pdf/2301.06617"]}
{"year":"2023","title":"Classifying European Court of Human Rights Cases Using Transformer-Based Techniques","authors":["AS Imran, H Hodnefjeld, Z Kastrati, N Fatima… - IEEE Access, 2023"],"snippet":"In the field of text classification, researchers have repeatedly shown the value of transformer-based models such as Bidirectional Encoder Representation from Transformers (BERT) and its variants. Nonetheless, these models are expensive in …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10130544.pdf"]}
{"year":"2023","title":"Clever little tricks: A socio-technical history of text-to-image generative models","authors":["K Steinfeld - International Journal of Architectural Computing, 2023"],"snippet":"The emergence of text-to-image generative models (eg, Midjourney, DALL-E 2, Stable Diffusion) in the summer of 2022 impacted architectural visual culture suddenly, severely, and seemingly out of nowhere. To contextualize this …","url":["https://journals.sagepub.com/doi/pdf/10.1177/14780771231168230"]}
{"year":"2023","title":"Clustering of Monolingual Embedding Spaces","authors":["K Bhowmik, A Ralescu - Digital, 2023"],"snippet":"Suboptimal performance of cross-lingual word embeddings for distant and low-resource languages calls into question the isomorphic assumption integral to the mapping-based methods of obtaining such embeddings. This paper investigates the comparative …","url":["https://www.mdpi.com/2673-6470/3/1/4"]}
{"year":"2023","title":"CNN-Fusion: An Effective and Lightweight Phishing Detection Method Based on Multi-Variant ConvNet","authors":["M Hussain, C Cheng, R Xu, M Afzal - Information Sciences, 2023"],"snippet":"Phishing scams are increasing as the technical skills and costs of phishing attacks diminish, emphasizing the need for rapid, precise, and low-cost prevention measures. Based on a character-level convolutional neural network (CNN), we present CNN-Fusion …","url":["https://www.sciencedirect.com/science/article/pii/S0020025523002281"]}
{"year":"2023","title":"Co $^ 2$ PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning","authors":["X Dong, Z Zhu, Z Wang, M Teleki, J Caverlee - arXiv preprint arXiv:2310.12490, 2023"],"snippet":"… cupation classification from the Common Crawl corpus. We report the overall accuracy of the task as well as the accuracy breakdown based on gender. To quantify gender bias, we compute the difference in true positive rates (TPR) between …","url":["https://arxiv.org/pdf/2310.12490"]}
{"year":"2023","title":"COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks","authors":["F Jourdan, A Picard, T Fel, L Risser, JM Loubes… - arXiv preprint arXiv …, 2023"],"snippet":"Transformer architectures are complex and their use in NLP, while it has engendered many successes, makes their interpretability or explainability challenging. Recent debates have shown that attention maps and attribution …","url":["https://arxiv.org/pdf/2305.06754"]}
{"year":"2023","title":"CODAMOSA: Escaping Coverage Plateaus in Test Generation with Pre-trained Large Language Models","authors":["C Lemieux, JP Inala, SK Lahiri, S Sen - 45th International Conference on Software …, 2023"],"snippet":"… For instance, GPT-3 [16] was trained on almost 700 GB of data collected from CommonCrawl [21]. Following the success of LLMs at natural language tasks, there has been tremendous interest in applying LLMs to code. This led to the development …","url":["https://www.carolemieux.com/codamosa_icse23.pdf"]}
{"year":"2023","title":"Code-switching input for machine translation: a case study of Vietnamese–English data","authors":["L Nguyen, O Mayeux, Z Yuan - International Journal of Multilingualism, 2023"],"snippet":"Multilingualism presents both a challenge and an opportunity for Natural Language Processing, with code-switching representing a particularly interesting problem for computational models trained on monolingual datasets. In this paper, we explore …","url":["https://www.tandfonline.com/doi/full/10.1080/14790718.2023.2224013"]}
{"year":"2023","title":"CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model","authors":["P Di, J Li, H Yu, W Jiang, W Cai, Y Cao, C Chen… - arXiv preprint arXiv …, 2023"],"snippet":"… The Chinese corpus is sourced from CommonCrawl, computer-related websites, documentation of programming languages and their third-party libraries, etc. The English corpus is sampled from various categories in Pile including StackExchange, …","url":["https://arxiv.org/pdf/2310.06266"]}
{"year":"2023","title":"CogAgent: A Visual Language Model for GUI Agents","authors":["W Hong, W Wang, Q Lv, J Xu, W Yu, J Ji, Y Wang… - arXiv preprint arXiv …, 2023"],"snippet":"… To facilitate robust training in GUI grounding, we have constructed the CCS400K (Common Crawl Screenshot 400K) dataset. This extensive dataset is formed by extracting URLs from the latest Common Crawl data, followed by capturing 400,000 web page …","url":["https://arxiv.org/pdf/2312.08914"]}
{"year":"2023","title":"Collaborative Graph Neural Networks for Attributed Network Embedding","authors":["Q Tan, X Zhang, X Huang, H Chen, J Li, X Hu - arXiv preprint arXiv:2307.11981, 2023"],"snippet":"… The posts are preprocessed into 602-dimensional feature vectors via Glove CommonCrawl world embedding [122]. Hence, node attributes refer to the 602 latent dimensions. We use the communities or ‘subreddit’ that the post belongs to a target label. …","url":["https://arxiv.org/pdf/2307.11981"]}
{"year":"2023","title":"Collecting and Predicting Neurocognitive Norms for Mandarin Chinese","authors":["YYH Le Qiu, E Chersoni"],"snippet":"… The results in Table 4 reveal that embedding models based on FastText and Skip Gram had highly significant correlations with human scores, and that the FastText vectors trained on Common Crawl achieved higher scores than did any of the ones …","url":["https://iwcs.pimoid.fr/7.pdf"]}
{"year":"2023","title":"COLLIE: Systematic Construction of Constrained Text Generation Tasks","authors":["S Yao, H Chen, AW Hanjie, R Yang, K Narasimhan - arXiv preprint arXiv:2307.08689, 2023"],"snippet":"Text generation under constraints have seen increasing interests in natural language processing, especially with the rapidly improving capabilities of large language models. However, existing benchmarks for constrained generation usually …","url":["https://arxiv.org/pdf/2307.08689"]}
{"year":"2023","title":"Combating Hate: How Multilingual Transformers Can Help Detect Topical Hate Speech","authors":["T Srikissoon, V Marivate - EPiC Series in Computing, 2023"],"snippet":"Automated hate speech detection is important to protecting people’s dignity, online experiences, and physical safety in Society 5.0. Transformers are sophisticated pretrained language models that can be fine-tuned for multilingual hate speech …","url":["https://login.easychair.org/publications/download/28NM"]}
{"year":"2023","title":"Common Crawl : Data Collection and Use Cases for NLP","authors":["S Nagel"],"snippet":"Crawler Politeness Implications •(with well-written robots. txt) less of• private/personal content• duplicated content• significant parts of the web (eg. social media) are not included• links in disallowed content are not visible to the crawler• easy-to-adapt …","url":["http://nlpl.eu/skeikampen23/nagel.230206.pdf"]}
{"year":"2023","title":"CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images","authors":["A Gokaslan, AF Cooper, J Collins, L Seguin… - arXiv preprint arXiv …, 2023"],"snippet":"We assemble a dataset of Creative-Commons-licensed (CC) images, which we use to train a set of open diffusion models that are qualitatively competitive with Stable Diffusion 2 (SD2). This task presents two challenges: (1) high-resolution CC images …","url":["https://arxiv.org/pdf/2310.16825"]}
{"year":"2023","title":"Community Competition and Political Extremism","authors":["C Henry"],"snippet":"… Second, the LLaMa 1 foundational models are trained on publicly available data sources including the CommonCrawl. The … the 30 seed users used to build the community dataset is present in the CommonCrawl corpus. Accuracy, precision, and …","url":["https://henryhenryhenry.com/Henry_JMP_915.pdf"]}
{"year":"2023","title":"Company Similarity using Large Language Models","authors":["D Vamvourellis, M Toth, S Bhagat, D Desai, D Mehta… - arXiv preprint arXiv …, 2023"],"snippet":"… It has been trained on multiple data sources like Common crawl dataset (around 600 billion words of text), GitHub dataset (100 million code repository), Stack overflow dataset (170 million questions and answers) on the task of next word …","url":["https://arxiv.org/pdf/2308.08031"]}
{"year":"2023","title":"Comparative Analysis of Balanced Code Smell Detection Using Machine Learning Check for updates","authors":["M Sabharwal, A Gupta, R Gandhi, I Khan - … : Proceedings of the International Conference on …"],"snippet":"… Any website which enables API calls to it can be used to collect data or for a more comprehensive analysis, Common Crawl by AWS can be used [5]. The scraped data will be extracted using a local script ran using the python requests library from the …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=033lEAAAQBAJ&oi=fnd&pg=PA371&dq=commoncrawl&ots=06-pLbuKv9&sig=8qoh4Hy7QynXXofSNrnXdYyDkrE"]}
{"year":"2023","title":"Comparative Analysis of Machine Learning and Deep Learning Models for Sentiment Analysis in Somali","authors":["AA Abdirahman, AO Hashi, MA Elmi, OER Rodriguez"],"snippet":"Understanding and analysing sentiment in user-generated content has become crucial with the increasing use of social media and online platforms. However, sentiment analysis in less-resourced languages like Somali poses unique …","url":["https://simad.edu.so/wp-content/uploads/2023/08/IJEEE-V10I7P104.pdf"]}
{"year":"2023","title":"Comparing different search methods for the open access journal recommendation tool B! SON","authors":["E Entrup, A Eppelin, R Ewerth, J Hartwig, M Tullney… - International Journal on …, 2023"],"snippet":"Finding a suitable open access journal to publish academic work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of predatory publishers …","url":["https://link.springer.com/article/10.1007/s00799-023-00372-3"]}
{"year":"2023","title":"Comparing Different Transformer Models' Performance for Identifying Toxic Language Online","authors":["C Sundelin - 2023"],"snippet":"There is a growing use of the internet and alongside that, there has been an increase in the use of toxic language towards other people that can be harmful to those that it targets. The usefulness of artificial intelligence has exploded in recent …","url":["https://www.diva-portal.org/smash/get/diva2:1784346/FULLTEXT01.pdf"]}
{"year":"2023","title":"Comparing the Similarity of OpenAPI-Based Microservices","authors":["Z Lu, DT Delaney, D Lillis - 2024"],"snippet":"Microservices constitute the state of the art for implementing distributed systems and have been seen as a potential solution towards open systems. The characteristics of open systems require structured microservice management, including grouping …","url":["https://lill.is/pubs/Lu2024.pdf"]}
{"year":"2023","title":"Comparison of Pre-trained vs Custom-trained Word Embedding Models for Word Sense Disambiguation","authors":["MF Ullah, A Saeed, N Hussain - ADCAIJ: Advances in Distributed Computing and …, 2023"],"snippet":"… First, the pre-trained model by Facebook1, trained on Common Crawl with vector dimension size 300, and a context window of size 5. Second, pre-trained by Khurram (Kanwal et al., 2019) with a vector dimension size of 300, and a context …","url":["https://revistas.usal.es/cinco/index.php/2255-2863/article/download/31084/29918"]}
{"year":"2023","title":"Comparison of the Three Algorithms for Concreteness Rating Estimation of English Words","authors":["VV Bochkarev, SV Khristoforov, AV Shevlyakova… - Acta Polytechnica …, 2022"],"snippet":"… In our case, the size of the CommonCrawl corpus that was used to obtain fastText vector … If we used a corpus which 3 times exceeds the size of CommonCrawl, we would probably … and the use of fastText vectors obtained on the CommonCrawl …","url":["http://acta.uni-obuda.hu/Bochkarev_Khristoforov_Shevlyakova_Solovyev_128.pdf"]}
{"year":"2023","title":"Comparison of Websites Employing Search Engine Optimization and Live Data","authors":["S Maitra, L Sahoo, S Sen, K Tiwary - Journal of Computer Science Research, 2023"],"snippet":"This study compares websites that take live data into account using search engine optimization (SEO). A series of steps called search engine optimization can help a website rank highly in search engine results. Static websites and dynamic websites …","url":["https://journals.bilpubgroup.com/index.php/jcsr/article/download/5536/4811"]}
{"year":"2023","title":"Complementing Scale: Novel Guidance Methods for Improving Language Models","authors":["O Press - 2023"],"snippet":"Abstract Language models (LMs) are at the core of almost all state of the art natural language processing systems. Recent papers, such as Brown et al.[2020] and Hoffmann et al.[2022] have shown that scaling up the size of these models leads to …","url":["https://search.proquest.com/openview/8d271a761db01c7dedf8f2619eff8b75/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Complex business ecosystem intelligence using AI-powered visual analytics","authors":["RC Basole, H Park, CD Seuss - Decision Support Systems, 2023"],"snippet":"Business ecosystems are complex, dynamic systems characterized by a multitude of entities, including companies, ventures, and technologies, as well as activities and trends. Understanding the state of business ecosystems is an increasingly critical …","url":["https://www.sciencedirect.com/science/article/pii/S0167923623002087"]}
{"year":"2023","title":"Comprehensive Evaluation of ChatGPT Reliability Through Multilingual Inquiries","authors":["PCR Puttaparthi, SS Deo, H Gul, Y Tang, W Shang… - arXiv preprint arXiv …, 2023"],"snippet":"… First, we recorded languages included in the Common Crawl [8] documentation—a pivotal open-source dataset widely used in the training of ChatGPT. Then, we built a list of languages supported by Google Cloud Translation, which is our chosen …","url":["https://arxiv.org/pdf/2312.10524"]}
{"year":"2023","title":"Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt","authors":["T PROMPT","Z Xu, Z Liu, B Chen, Y Tang, J Wang, K Zhou, X Hu… - arXiv preprint arXiv …, 2023"],"snippet":"While the numerous parameters in Large Language Models (LLMs) contribute to their superior performance, this massive scale makes them inefficient and memory-hungry. Thus, they are hard to deploy on the commodity hardware, such as one single GPU …","url":["https://arxiv.org/pdf/2305.11186","https://openreview.net/pdf?id=Gdm87rRjep"]}
{"year":"2023","title":"Computational Models for Understanding Narrative","authors":["N Montfort, RP y Pérez - Revista de Comunicação e Linguagens, 2023"],"snippet":"Descrevemos como a modelagem computacional da narrativa serve como um método de investigação e ajuda a aprofundar a compreensão humanística neste domínio. O nosso foco está em nossos próprios sistemas, MEXICA e Curveship …","url":["https://rcl.fcsh.unl.pt/index.php/rcl/article/download/247/199"]}
{"year":"2023","title":"Computational Study of News Systems: Embracing the Complexity Paradigm","authors":["N Hagar - 2023"],"snippet":"The production and spread of digital news involves a wide range of actors: journalists and the organizations that employ them, social media platforms, audiences, and myriad commentators, citizen journalists, bloggers, and other actors …","url":["https://search.proquest.com/openview/d07c9c4398e56c771c48792717cbd223/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Conclusions and Future Research","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"… The developers of XLM-Roberta and mT5 used different strategies to create “clean” subsets of the Common Crawl, while the two models are also based on different architectures. What is the impact of the difference in the architectures versus the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_8"]}
{"year":"2023","title":"Configuration Validation with Large Language Models","authors":["X Lian, Y Chen, R Cheng, J Huang, P Thakkar, T Xu"],"snippet":"Misconfigurations are the major causes of software failures. Existing configuration validation techniques rely on manually written rules or test cases, which are expensive to implement and maintain, and are hard to be comprehensive …","url":["https://yinfangchen.github.io/assets/pdf/ciri_paper.pdf"]}
{"year":"2023","title":"Constructing Multilingual Code Search Dataset Using Neural Machine Translation","authors":["R Sekizawa, N Duan, S Lu, H Yanaka - arXiv preprint arXiv:2306.15604, 2023"],"snippet":"Code search is a task to find programming codes that semantically match the given natural language queries. Even though some of the existing datasets for this task are multilingual on the programming language side, their query data are only in English …","url":["https://arxiv.org/pdf/2306.15604"]}
{"year":"2023","title":"Constructing Temporal Dynamic Knowledge Graphs from Interactive Text-based Games","authors":["KP Yu - arXiv preprint arXiv:2311.01928, 2023"],"snippet":"… embedding layer, which is initialized using the 300-dimensional fastText [6] word embeddings pretrained on Common Crawl (600B tokens). Lintext is a linear layer that reduces the dimension of the word embeddings to H, which is the dimension of …","url":["https://arxiv.org/pdf/2311.01928"]}
{"year":"2023","title":"Content still matters. A machine learning model for predicting news longevity from textual and context features","authors":["K Rybinski - Information Processing & Management, 2023"],"snippet":"There is an ongoing debate about what is more important in the modern online media newsroom, whether it is the news content and worthiness, or the audience clicks. Using a dataset of over one million articles from five countries (Belarus …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323001358"]}
{"year":"2023","title":"CONTENT-BASED CHARACTERIZATION OF THE END OF TERM WEB ARCHIVE","authors":["ME Phillips, KK Phillips, S Alam - iPRES 2023, 2023"],"snippet":"… This work is expected to continue to leverage existing tools and processes developed by Common Crawl for graph generation. With the … Likewise, this project leaned heavily upon the prior work of the Common Crawl team and adopted their …","url":["https://www.ideals.illinois.edu/items/128295/bitstreams/428955/data.pdf"]}
{"year":"2023","title":"Context Sensitive Tamil Language Spellchecker Using RoBERTa","authors":["R Rajalakshmi, V Sharma - Speech and Language Technologies for Low …, 2023"],"snippet":"… In our spellchecker model, we have used xlm-roberta-base model which is a pre-trained model on 2.5 TB of filtered CommonCrawl data containing 100 languages. Our spellchecker takes an input text, finds out the misspelled word and lists out the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-33231-9_4"]}
{"year":"2023","title":"CONTEXT-AND/OR FREQUENCY","authors":["R Delmonte, N Busetto"],"snippet":"… We used BERT – with the Italian model taken from UWAC corpus, Umberto-commoncrawl - and examined the output of the first or projection layer3. In this way we intended to check the predicting ability of BERT on the masked word, by selecting in turn one …","url":["https://www.csitcp.org/paper/12/1218csit18.pdf"]}
{"year":"2023","title":"Context-aware Swedish Lexical Simplification: Using pre-trained language models to propose contextually fitting synonyms","authors":["E Graichen - 2023"],"snippet":"This thesis presents the development and evaluation of context-aware Lexical Simplification (LS) systems for the Swedish language. In total three versions of LS models, LäsBERT, LäsBERT-baseline, and LäsGPT, were created and evaluated on …","url":["https://www.diva-portal.org/smash/get/diva2:1767273/FULLTEXT01.pdf"]}
{"year":"2023","title":"Contextualizing the Limits of Model & Evaluation Dataset Curation on Semantic Similarity Classification Tasks","authors":["D Theron - arXiv preprint arXiv:2311.04927, 2023"],"snippet":"This paper demonstrates how the limitations of pre-trained models and open evaluation datasets factor into assessing the performance of binary semantic similarity classification tasks. As (1) end-user-facing documentation around the …","url":["https://arxiv.org/pdf/2311.04927"]}
{"year":"2023","title":"Contextually Enriched Meta-Learning Ensemble Model for Urdu Sentiment Analysis","authors":["K Ahmed, MI Nadeem, D Li, Z Zheng, N Al-Kahtani… - Symmetry, 2023"],"snippet":"… On the other hand, this model makes use of pre-trained word vectors that were trained on “common crawl” and “Wikipedia” through the use of the fastText model [82]. The CBOW algorithm with position-weighting is used to train this word vector. After …","url":["https://www.mdpi.com/2073-8994/15/3/645/pdf"]}
{"year":"2023","title":"Continual Pre-Training of Large Language Models: How to (re) warm your model?","authors":["K Gupta, B Thérien, A Ibrahim, ML Richter, Q Anthony…"],"snippet":"Large language models (LLMs) are routinely pretrained on billions of tokens, only to restart the process over again once new data becomes available. A much cheaper and more efficient solution would be to enable the continual pre-training of these …","url":["https://openreview.net/pdf?id=pg7PUJe0Tl"]}
{"year":"2023","title":"Contributions to Neural Theorem Proving","authors":["JM Han - 2023"],"snippet":"In this dissertation we present several contributions to the nascent field of neural theorem proving, deep learning-driven automated theorem proving over large libraries of formalized mathematics. We work primarily with the Lean theorem prover …","url":["http://d-scholarship.pitt.edu/43969/19/Han%20-%20ETD%20-%202.pdf"]}
{"year":"2023","title":"Contributions to the video captioning in an open-world scenario using deep learning techniques","authors":["AS Inácio - 2023"],"snippet":"Video captioning poses a significant challenge within the Computer Vision and Artificial Intelligence domains. It involves the challenging task of translating the visual content of videos into natural language descriptions. Despite significant …","url":["http://repositorio.utfpr.edu.br/jspui/bitstream/1/32638/1/contributionsvideocaptioningopenworld.pdf"]}
{"year":"2023","title":"Controllable sentence simplification in Swedish: Automatic simplification of sentences using control prefixes and mined Swedish paraphrases","authors":["J Monsen - 2023"],"snippet":"… snapshots using CC-Net [62], an open-source repository with tools to download and clean Common Crawl snapshots. Common Crawl is a non-profit organization that collects and freely provides vast amounts of data from the web, including web …","url":["https://www.diva-portal.org/smash/get/diva2:1766696/FULLTEXT01.pdf"]}
{"year":"2023","title":"Conversation Analysis for Computational Modelling of Task-oriented Dialogue","authors":["N Duran - 2023"],"snippet":"Current methods of dialogue modelling for Conversational AI (CAI) bear little resemblance to the manner in which humans organise conversational interactions. The way utterances are represented, interpreted, and generated are determined by …","url":["https://uwe-repository.worktribe.com/preview/10485570/Conversation%20Analysis%20for%20Computational%20Modelling%20of%20%20Task-oriented%20Dialogue.pdf"]}
{"year":"2023","title":"Convolutional neural network approach for anomaly-based intrusion detection on IoT-enabled smart space orchestration system","authors":["V Upman, N Goranin, A Čenys - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:148980058/148980058.pdf"]}
{"year":"2023","title":"Corpus Modeling and the Geometries of Text: Meaning Spaces as Metaphor and Method","authors":["DS Stoltz, MA Taylor, MA Combs - 2023"],"snippet":"We explore the theoretical implications of spatial metaphors in the field of computational text analysis and inspect how the properties of topologies aid and inhibit our theories of textual meaning. Rather than mining for “ground truth” …","url":["https://osf.io/z4eyw/download"]}
{"year":"2023","title":"Countering Malicious Content Moderation Evasion in Online Social Networks: Simulation and Detection of Word Camouflage","authors":["Á Huertas-García, A Martín, JH Tato, D Camacho - arXiv preprint arXiv:2212.14727, 2022"],"snippet":"Content moderation is the process of screening and monitoring user-generated content online. It plays a crucial role in stopping content resulting from unacceptable behaviors such as hate speech, harassment, violence against specific groups …","url":["https://arxiv.org/pdf/2212.14727"]}
{"year":"2023","title":"CPG-LS: Causal Perception Guided Linguistic Steganography","authors":["L Xiang, J Xia, Y Liu, Y Gui - IEEE Signal Processing Letters, 2023"],"snippet":"… Experimental Settings 1) Dataset: A total of 10000 original English texts are randomly selected from the CC-100[27] corpus, which comprises a vast collection of high-quality datasets extracted from the Common Crawl. Each text treated as a cover …","url":["https://ieeexplore.ieee.org/abstract/document/10315184/"]}
{"year":"2023","title":"Creating Web-Scale, Annotated Document Understanding Datasets Tailored to Downstream Tasks: An Extension and Validation Study of the WordScape Data …","authors":["V Thanner - 2023"],"snippet":"… As the WordScape pipeline utilizes CommonCrawl purely to find URLs to downloadable Word documents, only .WAT files (containing … ) are extracted from the CommonCrawl metadata. This initial phase requires the downloading of up to …","url":["https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/634893/Thanner_Valdemar.pdf?sequence=1"]}
{"year":"2023","title":"Creative Use of OpenAI in Education: Case Studies from Game Development","authors":["F French, D Levi, C Maczo, A Simonaityte… - Multimodal Technologies …, 2023"],"snippet":"… A similar problem occurs with text output because many large generative AI models (LGAIMs), including GPT, have been trained on a vast amount of historical Internet data drawn from the ‘Common Crawl’ publicly available dataset [25], as well …","url":["https://www.mdpi.com/2414-4088/7/8/81"]}
{"year":"2023","title":"CreoleVal: Multilingual Multitask Benchmarks for Creoles","authors":["H Lent, K Tatariya, R Dabre, Y Chen, M Fekete… - arXiv preprint arXiv …, 2023"],"snippet":"Creoles represent an under-explored and marginalized group of languages, with few available resources for NLP research. While the genealogical ties between Creoles and other highly-resourced languages imply a significant potential for …","url":["https://arxiv.org/pdf/2310.19567"]}
{"year":"2023","title":"Critical Perspectives: A Benchmark Revealing Pitfalls in PerspectiveAPI","authors":["L Piedras, L Rosenblatt, J Wilkins - arXiv preprint arXiv:2301.01874, 2023","L Rosenblatt, L Piedras, J Wilkins - Proceedings of the Second Workshop on NLP for …, 2022"],"snippet":"Detecting “toxic” language in internet content is a pressing social and technical challenge. In this work, we focus on Perspective API from Jigsaw, a state-of-the-art tool that promises to score the “toxicity” of text, with a recent model update that …","url":["https://aclanthology.org/2022.nlp4pi-1.2.pdf","https://arxiv.org/pdf/2301.01874"]}
{"year":"2023","title":"Critical Theory of AI","authors":["S Lindgren - 2023"],"snippet":"We live in an age of artificial intelligence. Machines think and act in ever more complex ways, making suggestions and decisions on our behalf. While AI might be seen as practical and profitable, issues of data surveillance, algorithmic control, and …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=u7LdEAAAQBAJ&oi=fnd&pg=PA11&dq=commoncrawl&ots=aPc0Le2ohZ&sig=LRNUtvHxDy_gad1wDnEgOmp6wkA"]}
{"year":"2023","title":"Cross-Genre Argument Mining: Can Language Models Automatically Fill in Missing Discourse Markers?","authors":["G Rocha, HL Cardoso, J Belouadi, S Eger - arXiv preprint arXiv:2306.04314, 2023"],"snippet":"Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has …","url":["https://arxiv.org/pdf/2306.04314"]}
{"year":"2023","title":"Cross-Lingual Approaches for Text Generation Tasks in Low-Resource Languages","authors":["S Sagare - 2023"],"snippet":"… A challenge to this approach is that such web content is itself very sparse in low-resource languages, as can be observed in publicly available large dumps like CommonCrawl [69]. Hence, it is impossible to build monolingual parallel datasets in …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.b381ab529cae1ddb.736869767072617361645f7468657369732e706466.pdf"]}
{"year":"2023","title":"Cross-lingual Aspect-level Sentiment Classification with Graph Neural Network","authors":["鲍小异， 姜晓彤， 王中卿， 周国栋 - Journal of Software, 2023"],"snippet":": 目前, 在属性级情感分类任务上较为成熟的有标注数据集均为英文数据集, 而有标注的 中文数据集较少. 为了能够更好地利用规模庞大但却缺乏成熟标注数据的中文语言数据 集, 针对跨语言属性级情感分类任务进行了研究. 在跨语言属性级情感分类中, 一个核心 …","url":["http://www.jos.org.cn/josen/article/pdf/6667"]}
{"year":"2023","title":"Cross-lingual Classification of Crisis-related Tweets Using Machine Translation","authors":["S Al Amer, M Lee, P Smith - Proceedings of the 14th International Conference on …, 2023"],"snippet":"Utilisation of multilingual language models such as mBERT and XLM-RoBERTa has increasingly gained attention in recent work by exploiting the multilingualism of such models in different downstream tasks across different languages. However …","url":["https://aclanthology.org/2023.ranlp-1.3.pdf"]}
{"year":"2023","title":"Cross-lingual Machine Translation","authors":["GB Mohan, RP Kumar, NL Keerthana, D Mukesh… - Proceedings of Third …, 2023"],"snippet":"… There are 2.5 TB of unlabeled text in 100 languages extracted from the Common Crawl databases. Based on the ROBERTa methodology, … language model, and it has 2.5 TB of freshly constructed clean Common Crawl data in 100 languages. It …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=8DTYEAAAQBAJ&oi=fnd&pg=PA80&dq=commoncrawl&ots=whOf1YuF1W&sig=3RLgLGMCe-IZfoyDfrL1qt8Vjwk"]}
{"year":"2023","title":"Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages","authors":["L Qin, Q Chen, F Wei, S Huang, W Che - arXiv preprint arXiv:2310.14799, 2023"],"snippet":"… Therefore, we examine the language distribution (refer to Figure 8) in the widely used multilingual pretraining dataset, Common Crawl 2021. Based on the proportions, we incrementally integrated languages in descending and ascending …","url":["https://arxiv.org/pdf/2310.14799"]}
{"year":"2023","title":"Cross-lingual Sentence Embedding for Low-resource Chinese-Vietnamese Based on Contrastive Learning","authors":["Y Huang, Y Liang, Z Wu, E Zhu, Z Yu - ACM Transactions on Asian and Low …, 2023"],"snippet":"… And it was pre-trained on a new Common Crawl-based dataset covering 101 languages. mT5 inherits all of the benefits of T5 , such as its general-purpose text-to-text format, its design based on insights from a large-scale empirical study, and its scale. …","url":["https://dl.acm.org/doi/pdf/10.1145/3589341"]}
{"year":"2023","title":"Cross-Lingual Sentiment Analysis: A Survey","authors":["X Yuemei, C Han, W Wenqing, D Wanze, X Chengyang - Data Analysis and …, 2023"],"snippet":"[Objective] This paper teases out the research context of cross-lingual sentiment analysis (CLSA).[Coverage] We searched “TS= cross lingual sentiment OR cross lingual word embedding” in Web of Science database and 90 representative papers …","url":["https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/article/downloadArticleFile.do?attachType=PDF&id=5556"]}
{"year":"2023","title":"Cross-Lingual Text Reuse Detection at Document Level for English-Urdu Language Pair","authors":["M Sharjeel, I Muneer, S Nosheen, RMA Nawab… - ACM Transactions on Asian …, 2023"],"snippet":"In recent years, the problem of Cross-Lingual Text Reuse Detection (CLTRD) has gained the interest of the research community due to the availability of large digital repositories and automatic Machine Translation (MT) systems. These systems are …","url":["https://dl.acm.org/doi/pdf/10.1145/3592761"]}
{"year":"2023","title":"Cross-lingual Transfer Can Worsen Bias in Sentiment Analysis","authors":["S Goldfarb-Tarrant, B Ross, A Lopez - arXiv preprint arXiv:2305.12709, 2023"],"snippet":"… Since our pre-training data is from Wikipedia and CommonCrawl, Paracrawl, or the target language equivalent, there is a domain shift between pre-training and fine-tuning data, and between fine-tuning and evaluation data, which are more similar to the pretraining; …","url":["https://arxiv.org/pdf/2305.12709"]}
{"year":"2023","title":"Cross-Lingual Transfer Learning for Misinformation Detection: Investigating Performance Across Multiple Languages","authors":["O Ozcelik, AS Yenicesu, O Yildirim, DS Haliloglu… - Proceedings of the 4th …, 2023"],"snippet":"… Indeed, 100 languages from 2.5TB of filtered CommonCrawl data were used as its pre-training material. In order to learn embedded representations of multilingual texts, XLM-R employs an unsupervised learning technique. This makes it possible to …","url":["https://aclanthology.org/2023.ldk-1.59.pdf"]}
{"year":"2023","title":"Cross-lingual Transfer Learning with Persian","authors":["S Mollanorozy, M Tanti, M Nissim"],"snippet":"The success of cross-lingual transfer learning for POS tagging has been shown to be strongly dependent, among other factors, on the (typological and/or genetic) similarity of the lowresource language used for testing and the language (s) used in …","url":["https://sigtyp.github.io/workshops/2023/sigtyp/papers/17_cross_lingual_transfer_learnin.pdf"]}
{"year":"2023","title":"Cross-Lingual Transfer of Cognitive Processing Complexity","authors":["C Pouw, N Hollenstein, L Beinborn - arXiv preprint arXiv:2302.12695, 2023"],"snippet":"When humans read a text, their eye movements are influenced by the structural complexity of the input sentences. This cognitive phenomenon holds across languages and recent studies indicate that multilingual language models utilize …","url":["https://arxiv.org/pdf/2302.12695"]}
{"year":"2023","title":"Cross-Modal Reasoning with Event Correlation for Video Question Answering","authors":["C Yin, Z Che, K Wu, Z Xu, Q Qiu, J Tang - arXiv preprint arXiv:2312.12721, 2023"],"snippet":"Video Question Answering (VideoQA) is a very attractive and challenging research direction aiming to understand complex semantics of heterogeneous data from two domains, ie, the spatio-temporal video content and the word sequence in question …","url":["https://arxiv.org/pdf/2312.12721"]}
{"year":"2023","title":"Cross-modal Transformer with Language Query for Referring Image Segmentation","authors":["W Zhang, Q Tan, P Li, Q Zhang, R Wang - Neurocomputing, 2023"],"snippet":"… As shown in row 2 in Table 5, we use Glove [65] pre-trained on Common Crawl 840B tokens instead of the randomly initialized word embeddings. We found that Glove improves the performance of CMT more than LSTM. …","url":["https://www.sciencedirect.com/science/article/pii/S0925231223002321"]}
{"year":"2023","title":"Cross-Multilingual, Cross-Lingual and Monolingual Transfer Learning For Arabic Dialect Sentiment Classification","authors":["N Boudad, R Faizi, ROH Thami - 2023"],"snippet":"Transfer learning have recently proven to be very powerful in diverse Natural language processing (NLP) tasks such as Machine translation, Sentiment Analysis, Question/Answering. In this work, we investigate the use of transfer learning (TL) in …","url":["https://www.researchsquare.com/article/rs-3167222/latest.pdf"]}
{"year":"2023","title":"Cross-portal metadata alignment-connecting open data portals through means of formal concept analysis","authors":["M Bogdanović, MF Gligorijević, N Veljković, D Puflović… - Information Sciences, 2023"],"snippet":"… The GloVe model we used in this research contains word vector space with meaningful substructure generated and trained on Common Crawl data. Training resulted in 840 billion generated tokens and vocabulary containing 2.2 million …","url":["https://www.sciencedirect.com/science/article/pii/S0020025523005273"]}
{"year":"2023","title":"Cross‐domain sentiment classification using decoding‐enhanced bidirectional encoder representations from transformers with disentangled attention","authors":["RK Singh, MK Sachan, RB Patel - Concurrency and Computation: Practice and …"],"snippet":"Cross‐domain sentiment classification is a significant task of sentiment analysis that objectives to predict the opinion orientation of text documents in the target domain by using the source domain's learned classifier. Most of the existing approaches of …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.7589"]}
{"year":"2023","title":"Crystal Ball for the Impact of Anthropogenic Climate Change on Global Air Quality PM 2.5","authors":["S Shan - Authorea Preprints, 2023"],"snippet":"Air pollution caused by PM2. 5 particles is a major global concern, particularly for human health. 19 This study used machine learning tools to uncover the social factors influencing PM2. 5 emissions. 20 Text mining techniques were employed to …","url":["https://www.authorea.com/doi/pdf/10.22541/essoar.169008274.43911108"]}
{"year":"2023","title":"CS 5968/6968: Data Str Alg Scalable Comp Spring 2023","authors":["PP Scribe, S Singh"],"snippet":"In this lecture, we will focus only on static graphs, where no insertions/deletions to the vertices would be made. An example of such a graph would be the SRA graph of a reference human genome. In the next lecture, we will extend our discussion to …","url":["https://users.cs.utah.edu/~pandey/courses/cs6968/spring23/notes/ScribeLec14.pdf"]}
{"year":"2023","title":"Cultural Adaptation of Recipes","authors":["Y Cao, Y Kementchedjhieva, R Cui, A Karamolegkou… - arXiv preprint arXiv …, 2023"],"snippet":"Building upon the considerable advances in Large Language Models (LLMs), we are now equipped to address more sophisticated tasks demanding a nuanced understanding of cross-cultural contexts. A key example is recipe adaptation, which …","url":["https://arxiv.org/pdf/2310.17353"]}
{"year":"2023","title":"CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages","authors":["T Nguyen, C Van Nguyen, VD Lai, H Man, NT Ngo… - arXiv preprint arXiv …, 2023"],"snippet":"The driving factors behind the development of large language models (LLMs) with impressive learning capabilities are their colossal model sizes and extensive training datasets. Along with the progress in natural language processing, LLMs …","url":["https://arxiv.org/pdf/2309.09400"]}
{"year":"2023","title":"Curricular Transfer Learning for Sentence Encoded Tasks","authors":["JMC de Sá, MF Sanches, RR de Souza, JC Reis… - arXiv preprint arXiv …, 2023"],"snippet":"Fine-tuning language models in a downstream task is the standard approach for many state-of-the-art methodologies in the field of NLP. However, when the distribution between the source task and target task drifts, \\textit{eg}, conversational …","url":["https://arxiv.org/pdf/2308.01849"]}
{"year":"2023","title":"Cyberbullying Detection in Social Networks: A Comparison between Machine Learning and Transfer Learning Approaches","authors":["TH Teng, KD Varathan - IEEE Access, 2023"],"snippet":"… For comparison purposes, this research employed pre-trained word vectors trained from tokens in Common Crawl, Wikipedia, and Twitter which come with several dimensions (100, 200). The word vectors are publicly available in the …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10122521.pdf"]}
{"year":"2023","title":"Czech-ing the News: Article Trustworthiness Dataset for Czech","authors":["M Bohacek, M Bravansky, F Trhlík, V Moravec - Proceedings of the 13th Workshop on …, 2023"],"snippet":"We present the Verifee dataset: a multimodal dataset of news articles with fine-grained trustworthiness annotations. We bring a diverse set of researchers from social, media, and computer sciences aboard to study this interdisciplinary problem holistically and …","url":["https://aclanthology.org/2023.wassa-1.10.pdf"]}
{"year":"2023","title":"D4: Improving LLM Pretraining via Document De-Duplication and Diversification","authors":["K Tirumala, D Simig, A Aghajanyan, A Morcos"],"snippet":"… We start with 5 CommonCrawl dumps 3 which range from 2017 to 2020. We then use CC-net (Wenzek … We note that since our dataset is curated from CommonCrawl dumps, there is risk that our training set … (2023), since we use the …","url":["https://dmlr.ai/assets/accepted-papers/131/CameraReady/LLM_Data_Pruning_Paper_Camera_Ready.pdf"]}
{"year":"2023","title":"Danish Foundation Models","authors":["K Enevoldsen, L Hansen, DS Nielsen, RAF Egebæk… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models, sometimes referred to as foundation models, have transformed multiple fields of research. However, smaller languages risk falling behind due to high training costs and small incentives for large companies to train …","url":["https://arxiv.org/pdf/2311.07264"]}
{"year":"2023","title":"Data Acquisition: A New Frontier in Data-centric AI","authors":["L Chen, B Acun, N Ardalani, Y Sun, F Kang, H Lyu… - arXiv preprint arXiv …, 2023"],"snippet":"As Machine Learning (ML) systems continue to grow, the demand for relevant and comprehensive datasets becomes imperative. There is limited study on the challenges of data acquisition due to ad-hoc processes and lack of consistent …","url":["https://arxiv.org/pdf/2311.13712"]}
{"year":"2023","title":"Data augmentation and generation for natural language processing","authors":["H Boulanger - 2023"],"snippet":"Natural Language Processing (NLP) is a rapidly growing field that deals with the interaction between computers and human language. One of the major challenges in NLP is dealing with low-resource scenarios, where limited amounts of labeled …","url":["https://www.theses.fr/2023UPASG019.pdf"]}
{"year":"2023","title":"Data Cartography for Low-Resource Neural Machine Translation","authors":["A Richburg, M Carpuat - Findings of the Association for Computational …, 2022"],"snippet":"While collecting or generating more parallel data is necessary to improve machine translation (MT) in low-resource settings, we lack an understanding of how the limited amounts of existing data are actually used to help guide the collection of …","url":["https://aclanthology.org/2022.findings-emnlp.410.pdf"]}
{"year":"2023","title":"Data Dialogue with ChatGPT: Using Code Interpreter to Simulate and Analyse Experimental Data","authors":["A Low, ZY Kalender - arXiv preprint arXiv:2311.12415, 2023"],"snippet":"Artificial intelligence (AI) has the potential to revolutionise many aspects of physics education, including introductory laboratory courses. In this study, we explored the capability of OpenAI's ChatGPT-4 to interpret and complete an introductory …","url":["https://arxiv.org/pdf/2311.12415"]}
{"year":"2023","title":"Data Distillation: A Survey","authors":["N Sachdeva, J McAuley - arXiv preprint arXiv:2301.04272, 2023"],"snippet":"… Textual data is available in large amounts from sources like websites, news articles, academic manuscripts, etc., and is also readily accessible with datasets like the common crawl1 which sizes up to almost 541TB. Furthermore, with the advent of …","url":["https://arxiv.org/pdf/2301.04272"]}
{"year":"2023","title":"Data Filtering Networks","authors":["A Fang, AM Jose, A Jain, L Schmidt, A Toshev… - arXiv preprint arXiv …, 2023"],"snippet":"… ), and gradually replace it with unfiltered data from Common Crawl until this pool only contains Common Crawl. We train DFNs on these data mixes, and use these DFNs to CLIP filter a separate pool of 128 million Common Crawl samples from …","url":["https://arxiv.org/pdf/2309.17425"]}
{"year":"2023","title":"Data Management For Large Language Models: A Survey","authors":["Z Wang, W Zhong, Y Wang, Q Zhu, F Mi, B Wang… - arXiv preprint arXiv …, 2023"],"snippet":"Data plays a fundamental role in the training of Large Language Models (LLMs). Effective data management, particularly in the formulation of a well-suited training dataset, holds significance for enhancing model performance and improving training …","url":["https://arxiv.org/pdf/2312.01700"]}
{"year":"2023","title":"Data Portraits: Recording Foundation Model Training Data","authors":["M Marone, B Van Durme - arXiv preprint arXiv:2303.03919, 2023"],"snippet":"Foundation models are trained on increasingly immense and opaque datasets. Even while these models are now key in AI system building, it can be difficult to answer the straightforward question: has the model already encountered a given …","url":["https://arxiv.org/pdf/2303.03919"]}
{"year":"2023","title":"Data Pruning for Efficient Model Pruning in Neural Machine Translation","authors":["A Azeemi, I Qazi, A Raza - Findings of the Association for Computational …, 2023"],"snippet":"… We use the T5-small variant pre-trained on the 750 GB C4 dataset containing text from the public web scrape of the common crawl. This variant has 60 million parameters, 6 layers in the encoder and decoder each, and 8-headed attention. …","url":["https://aclanthology.org/2023.findings-emnlp.18.pdf"]}
{"year":"2023","title":"Data Selection for Language Models via Importance Resampling","authors":["SM Xie, S Santurkar, T Ma, P Liang - arXiv preprint arXiv:2302.03169, 2023"],"snippet":"Selecting a suitable training dataset is crucial for both general-domain (eg, GPT-3) and domain-specific (eg, Codex) language models (LMs). We formalize this data selection problem as selecting a subset of a large raw unlabeled dataset to match a …","url":["https://arxiv.org/pdf/2302.03169"]}
{"year":"2023","title":"Data-Centric Debugging: mitigating model failures via targeted image retrieval","authors":["S Singla, AM Chegini, M Moayeri, S Feizi - Proceedings of the IEEE/CVF Winter …, 2024"],"snippet":"Deep neural networks can be unreliable in the real world when the training set does not adequately cover all the settings where they are deployed. Focusing on image classification, we consider the setting where we have an error distribution E …","url":["https://openaccess.thecvf.com/content/WACV2024/papers/Singla_Data-Centric_Debugging_Mitigating_Model_Failures_via_Targeted_Image_Retrieval_WACV_2024_paper.pdf"]}
{"year":"2023","title":"Data-Driven Approach to Automated Hypernym Hierarchy Construction for the Ukrainian WordNet","authors":["N Romanyshyn - 2023"],"snippet":"… The authors used publicly available data sources such as web pages scraped by CommonCrawl (67%), open source code repositories from GitHub, Wikipedia in 20 different languages, including Ukrainian, public domain books from Project …","url":["https://www.researchgate.net/profile/Nataliia-Romanyshyn/publication/372133776_Data-Driven_Approach_to_Automated_Hypernym_Hierarchy_Construction_for_the_Ukrainian_WordNet/links/64a5c44d8de7ed28ba7abad7/Data-Driven-Approach-to-Automated-Hypernym-Hierarchy-Construction-for-the-Ukrainian-WordNet.pdf"]}
{"year":"2023","title":"DATA-EFFICIENT LEARNING FOR HEALTHCARE QUERIES IN LOW-RESOURCE AND CODE MIXED LANGUAGE SETTINGS","authors":["S Mwongela, J Patel, S Rajasekharan, L Wotton…"],"snippet":"… MT5 is a multilingual variant of T5 that was pre-trained on a new Common Crawl-based dataset covering 101 languages (Xue et al., 2020). … It is pre-trained on 2.5TB of filtered Common Crawl data containing 100 languages. It was introduced in the …","url":["https://pml4dc.github.io/iclr2023/pdf/PML4DC_ICLR2023_40.pdf"]}
{"year":"2023","title":"Data-Juicer: A One-Stop Data Processing System for Large Language Models","authors":["D Chen, Y Huang, Z Ma, H Chen, X Pan, C Ge, D Gao… - arXiv preprint arXiv …, 2023"],"snippet":"… As an illustrative example, we describe our text quality classifier for culling high-quality text from heterogeneous data sources like CommonCrawl. This tool is a reproduced model based on the closed-source GPT-3 quality scorer [10]. Moreover, we have …","url":["https://arxiv.org/pdf/2309.02033"]}
{"year":"2023","title":"Data: A Critical Element for AI","authors":["T Taulli - ChatGPT and Bard for Business Automation: Achieving …, 2023"],"snippet":"… CommonCrawl News: This is a dataset of news stories from websites across the globe. …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-9852-7_8"]}
{"year":"2023","title":"Data: The Fuel for Generative AI","authors":["T Taulli - Generative AI: How ChatGPT and Other AI Tools Will …, 2023"],"snippet":"A large language model (LLM) processes huge amounts of data for its generative AI systems. They are on the scale of petabytes. Consider that a petabyte is 1000 terabytes. This would hold about 500 billion pages of standard text. No doubt, the …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-9367-6_2"]}
{"year":"2023","title":"Databases, Search Engines","authors":["BVV Martens - Keywords In and Out of Context, 2023"],"snippet":"… (2019) at OpenAI and pre-trained with the Common Crawl dataset, forms the current backbone of the Bing search engine. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-32530-4_9"]}
{"year":"2023","title":"DataComp: In search of the next generation of multimodal datasets","authors":["S Yitzhak Gadre, G Ilharco, A Fang, J Hayase… - arXiv e-prints, 2023","SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis… - arXiv preprint arXiv …, 2023"],"snippet":"… We provide a testbed for dataset experiments centered around a new candidate pool of 12.8B image-text pairs from Common Crawl. Participants in our benchmark design new filtering techniques or curate new data sources and then evaluate their …","url":["https://arxiv.org/pdf/2304.14108","https://ui.adsabs.harvard.edu/abs/2023arXiv230414108Y/abstract"]}
{"year":"2023","title":"Dataset Factory: A Toolchain For Generative Computer Vision Datasets","authors":["D Kharitonov, R Turner - arXiv preprint arXiv:2309.11608, 2023"],"snippet":"… As an illustrative example, the prestigious DataComp competition built around the Common Crawl data features four scale tracks (12.8M, 128M, 1.28B, and 12.8B samples [3]), but in the first few months, the leaderboard for the top two tracks have …","url":["https://arxiv.org/pdf/2309.11608"]}
{"year":"2023","title":"Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data","authors":["Y Yang, AK Singh, M Elhoushi, A Mahmoud… - arXiv preprint arXiv …, 2023"],"snippet":"… In this race for higher performance, some training datasets have swelled to petabyte size, sourced from extensive repositories like the Common Crawl. While significant effort has gone into optimizing the computational aspects of training LLMs …","url":["https://arxiv.org/pdf/2312.02418"]}
{"year":"2023","title":"Decomposing geographical judgments into spatial, temporal and linguistic components","authors":["D Gatti, G Anceresi, M Marelli, T Vecchi, L Rinaldi - 2023"],"snippet":"When mentally exploring large-scale maps, humans are assumed to mainly rely on spatial information derived from direct perceptual experience (eg, prior visual experience with the geographical map itself). In the present study, we rather tested …","url":["https://osf.io/preprints/psyarxiv/3a6tr/download"]}
{"year":"2023","title":"Deep Learning Algorithms for Cybersecurity Applications","authors":["S Takale, S Pawar, V Khot, VS Gutte, A Acharya"],"snippet":"… Around one million legitimate and phishing URLs were used on the dataset collected from PhishTank and Common Crawl. To build the IPDS, the LSTM and CNN classifier used over 10,000 images and one million URLs for training. The …","url":["https://www.researchgate.net/profile/Sayli-Takale/publication/374419058_Deep_Learning_Algorithms_for_Cybersecurity_Applications/links/651d010fb0df2f20a20e89f6/Deep-Learning-Algorithms-for-Cybersecurity-Applications.pdf"]}
{"year":"2023","title":"Deep learning and low-resource languages: How much data is enough? A case study of three linguistically distinct South African languages","authors":["R Eiselen, T Gaustad"],"snippet":"… data like Common Crawl or Wikipedia, which have some inherent limitations (as discussed later in this paper), but also have limited availability for South African languages. For instance, isiNdebele has no Wikipedia data and is therefore not …","url":["https://www.researchgate.net/profile/Tanja-Gaustad/publication/370953302_Deep_learning_and_low-resource_languages_How_much_data_is_enough_A_case_study_of_three_linguistically_distinct_South_African_languages/links/646c7da8ce39a956fbd02ca8/Deep-learning-and-low-resource-languages-How-much-data-is-enough-A-case-study-of-three-linguistically-distinct-South-African-languages.pdf"]}
{"year":"2023","title":"Deep Learning Benchmark Studies on an Advanced AI Engineering Testbed from the Open Compass Project","authors":["MY Wang, J Uran, P Buitrago - Practice and Experience in Advanced Research …, 2023"],"snippet":"We present the Open Compass project’s pilot deep learning benchmark results with various AI accelerators. Those accelerators are NVIDIA V-100 and A-100, AMD MI100, as well as emerging novel accelerators such as Cerebras CS-2 and …","url":["https://dl.acm.org/doi/pdf/10.1145/3569951.3597596"]}
{"year":"2023","title":"Deep learning for clinical texts in low-data regimes","authors":["D Chopard - 2023"],"snippet":"… noticed that FastText embeddings trained on Wikipedia performed worse than GloVe embeddings trained on the Common Crawl corpus. … Third, RoBERTa is trained on an about ten times larger dataset, which includes the Common Crawl-News …","url":["https://orca.cardiff.ac.uk/id/eprint/157748/1/PhD_Thesis_DaphneChopard_corrected_final_submission.pdf"]}
{"year":"2023","title":"Deep Learning Model for Automated Trainee Assessment During High-Fidelity Simulation","authors":["MD Siddiqui Asad, Z Zhoujie, P Chuer"],"snippet":"Problem: Implementation of competency-based medical education has necessitated more frequent trainee assessments. Use of simulation as an assessment tool is limited by access to trained examiners, cost, and concerns with interrater reliability …","url":["https://journals.lww.com/academicmedicine/_layouts/15/oaks.journals/downloadpdf.aspx?an=00001888-990000000-00469"]}
{"year":"2023","title":"Deep learning model for Mongolian Citizens Feedback Analysis using Word Vector Embeddings","authors":["Z Dashdorj, T Munkhbayar, S Grigorev - arXiv preprint arXiv:2302.12069, 2023"],"snippet":"… The vector model of words taught in Mongolian text on Wikipedia and Common Crawl, is 300-dimensional and contains 600,000 Mongolian words. The model was trained using CBOW with position weights with character n-grams of length 5, a …","url":["https://arxiv.org/pdf/2302.12069"]}
{"year":"2023","title":"Deep Learning Transformer Models for Building a Comprehensive and Real-time Trauma Observatory: Development and Validation Study","authors":["G Chenais, C Gil-Jardiné, H Touchais, MA Fernandez… - JMIR AI, 2023"],"snippet":"… BelGPT2 was the first GPT-2 model fine-tuned on a French heterogeneous corpus (CommonCrawl, French Wikipedia, and EuroParl) released on the Hugging Face platform. The self-supervised training of transformers in a specific domain can …","url":["https://ai.jmir.org/2023/1/e40843/"]}
{"year":"2023","title":"Deep Learning-based POS Tagger and Chunker for Odia Language Using Pre-trained Transformers","authors":["T Dalai, TK Mishra, PK Sa - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"Developing effective natural language processing (NLP) tools for low-resourced languages poses significant challenges. This article centers its attention on the task of Part-of-speech (POS) tagging and chunking, which pertains to the identification …","url":["https://dl.acm.org/doi/pdf/10.1145/3637877"]}
{"year":"2023","title":"Deepfake Detection on Social Media: Leveraging Deep Learning and FastText Embeddings for Identifying Machine-Generated Tweets","authors":["S Sadiq, T Aljrees, S Ullah - IEEE Access, 2023"],"snippet":"… 2) FastText Subword FastText Subword has 2 million word vectors that were learned using Common Crawl’s subword information (600B tokens). By breaking down each word into its component words, subword embedding gives us more …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10229120.pdf"]}
{"year":"2023","title":"Defeasible Reasoning with Large Language Models–Initial Experiments and Future Directions","authors":["G Antoniou, S Batsakis - 2023"],"snippet":"As Large Language Models gain prominence in the AI landscape, it is essential to understand their capabilities and limitations, among others in terms of reasoning. This paper is a first step towards understanding the capabilities in terms of …","url":["https://ceur-ws.org/Vol-3485/paper7687.pdf"]}
{"year":"2023","title":"Demystifying CLIP Data","authors":["H Xu, S Xie, XE Tan, PY Huang, R Howes, V Sharma… - arXiv preprint arXiv …, 2023"],"snippet":"Contrastive Language-Image Pre-training (CLIP) is an approach that has advanced research and applications in computer vision, fueling modern recognition systems and generative models. We believe that the main ingredient to the success of CLIP …","url":["https://arxiv.org/abs/2309.16671"]}
{"year":"2023","title":"Dense Information Retrieval on a Latin digital library via LaBSE and LatinBERT embeddings","authors":["FA Galatolo, G Martino, MGCA Cimino, CO Tommasi"],"snippet":"… The authors also demonstrated the effectiveness of the LaBSE model by mining parallel data from CommonCrawl repository and using it to train competitive Neural Machine Translation (NMT) models for English-Chinese and English-German. One …","url":["https://pubs.galatolo.me/galatololatin.pdf"]}
{"year":"2023","title":"Densest Subhypergraph: Negative Supermodular Functions and Strongly Localized Methods","authors":["Y Huang, DF Gleich, N Veldt - arXiv preprint arXiv:2310.13792, 2023"],"snippet":"Dense subgraph discovery is a fundamental primitive in graph and hypergraph analysis which among other applications has been used for real-time story detection on social media and improving access to data stores of social networking systems …","url":["https://arxiv.org/pdf/2310.13792"]}
{"year":"2023","title":"Deobfuscating Leetspeak With Deep Learning to Improve Spam Filtering","authors":["I Vélez de Mendizabal, X Vidriales, V Basto-Fernandes… - 2023"],"snippet":"The evolution of anti-spam filters has forced spammers to make greater efforts to bypass filters in order to distribute content over networks. The distribution of content encoded in images or the use of Leetspeak are concrete and clear examples of …","url":["https://reunir.unir.net/bitstream/handle/123456789/15131/ip2023_07_003.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"DEPARTMENT OF COMPUTER ENGINEERING","authors":["PCE Trust's"],"snippet":"Introduction to Web. Information Retrieval and Web Search.: Basic Concepts of Information Retrieval, Information Retrieval Methods–Boolean Model, Vector Space Model and Statistical Language Model, Relevance Feedback, Evaluation Measures …","url":["http://www.pccoepune.com/pdf/syllabi/M-Tech-Computer-syllabus.pdf"]}
{"year":"2023","title":"Depression clinical detection model based on social media: a federated deep learning approach","authors":["Y Liu - 2023"],"snippet":"… Specifically, a pre-processed Common Crawl dataset of more than 2TB based on 100 languages is used to train cross-language representations in a self-supervised manner. This includes generating new unlabeled corpora for low-resource …","url":["https://www.researchsquare.com/article/rs-2910523/latest"]}
{"year":"2023","title":"Design and Data Mining Techniques for Large-Scale Scholarly Digital Libraries and Search Engines","authors":["S Rohatgi - 2023"],"snippet":"The exponential growth of digital libraries and the proliferation of scholarly content in electronic formats have made data mining and information retrieval essential tools for effectively managing, organizing, and disseminating knowledge. This thesis …","url":["https://etda.libraries.psu.edu/files/final_submissions/28910"]}
{"year":"2023","title":"Designing a Multilingual Fact-Checking Dataset from Existing Question-Answering Data","authors":["D Kamenicky"],"snippet":"… To create a dataset, Common Crawl was used as a source of text. Due to the scraped text data a significant portion of it is not natural language. It consists of gibberish, duplicate text, menus, error messages, and other non-useful content. To …","url":["https://dspace.vutbr.cz/bitstream/handle/11012/211905/final-thesis.pdf?sequence=-1"]}
{"year":"2023","title":"Designing with Language: Wireframing UI Design Intent with Generative Large Language Models","authors":["S Feng, M Yuan, J Chen, Z Xing, C Chen - arXiv preprint arXiv:2312.07755, 2023"],"snippet":"… Since the training samples of LLMs are typically scraped from the raw web page data, eg, GPT was trained on 410 billion tokens from the Common Crawl web corpus, we use HTML syntax as the domain-specific language to convert the UI screens into …","url":["https://arxiv.org/pdf/2312.07755"]}
{"year":"2023","title":"Detecting Human Emotion by Text Classification.","authors":["U Brunda, P Akhilesh, K Kalaiselvi - Grenze International Journal of Engineering & …, 2023"],"snippet":"… Using more than two terabytes of filtered CommonCrawl data, we train a Transformer-based masked language model on 100 different languages. On a number of cross-lingual benchmarks, including +14.6% average accuracy on XNLI, +13 …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=23955287&AN=171360357&h=d%2F1IkrkL7uOWJhT1gMRrfuzsXlF%2BcB84%2B3mheYLZ33wHF9ijxRMsh5eJ52tl3CdG7qYQw%2FdcGArzp1oVlQjI6A%3D%3D&crl=c"]}
{"year":"2023","title":"Detecting Human Rights Violations on Social Media during Russia-Ukraine War","authors":["P Nemkova, S Ubani, SO Polat, N Kim, RD Nielsen - arXiv preprint arXiv:2306.05370, 2023"],"snippet":"… We also evaluated XLM-RoBERTa20, a transformer model pretrained on a large corpus in a self-supervised fashion on 2.5TB of filtered CommonCrawl data spanning 100 languages [12]. Finally, we also tried RuBERT, a BERT-based model …","url":["https://arxiv.org/pdf/2306.05370"]}
{"year":"2023","title":"Detecting Kids Cyberbullying Using Transfer Learning Approach: Transformer Fine-Tuning Models","authors":["WMS Yafooz, A Al-Dhaqm, A Alsaeedi - Kids Cybersecurity Using Computational …, 2023"],"snippet":"… XLMRoBERTa: This is a pertained model trained on 2.5 TB of text collected from Wikipedia and Common Crawl data of 100 languages including the Arabic language [38]. It is developed by Facebook and it contains a vocabulary size of 250 k. It has …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21199-7_18"]}
{"year":"2023","title":"Detecting Modern Maldocs: An Analytical Study of PDF Feature Importance Using KDD Cup 99 as the Process Framework","authors":["CA Streun - 2024"],"snippet":"… For instance, the Govdocs1 PDF corpus (Govdocs1 – Digital Corpora, nd) was the seminal corpus that laid the groundwork for future web crawls, and Common Crawl (Common Crawl - Open Repository of Web Crawl Data, nd) and SafeDocs (Allison et …","url":["https://search.proquest.com/openview/9d14303f969f105a5660ddbd9f4b64e6/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Detecting Natural Language Biases with Prompt-based Learning","authors":["MA Aowal, MT Islam, PM Mammen, S Shetty - arXiv preprint arXiv:2309.05227, 2023"],"snippet":"In this project, we want to explore the newly emerging field of prompt engineering and apply it to the downstream task of detecting LM biases. More concretely, we explore how to design prompts that can indicate 4 different types of biases: (1) …","url":["https://arxiv.org/pdf/2309.05227"]}
{"year":"2023","title":"Detecting Personal Information in Training Corpora: an Analysis","authors":["N Subramani, AS Luccioni, J Dodge, M Mitchell"],"snippet":"… This corpus consists of text taken from Common Crawl then passed through a number of filters with the intention of retaining high-quality English text The C4-en validation set of the C4 dataset that we analyzed was created by taking the April …","url":["https://trustnlpworkshop.github.io/papers/28.pdf"]}
{"year":"2023","title":"Detecting Phishing URLs through Deep Learning Models","authors":["S Noor, SU Bazai, S Tareen, S Ullah - … Applications: Volume One: Image Security and …, 2024"],"snippet":"… Kaggle Common Crawl, Common Crawl 2 Phish Tank, Alexa … PhishTank, ALEXA, and Common Crawl data sets are mostly used by authors for training models. For evaluating the model, the authors mostly used accuracy, precision, recall, and F1-score …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=BubpEAAAQBAJ&oi=fnd&pg=PA176&dq=commoncrawl&ots=r45P1BXabe&sig=kWgzaIy3lrVSqLjKTm5iTfnDxYE"]}
{"year":"2023","title":"Detecting Salient Antimetaboles in English Texts Using Deep and Transfer Learning","authors":["G Berthomet - 2023"],"snippet":"… In our case, we opted for GloVe24 in its Common Crawl (48B) version as our embedding software. We decided to use it because of its high result in other NLP tasks while being easy to access and use directly thanks to the existence of several …","url":["https://ca-roll.github.io/downloads/Berthomet_Masterarbeit___Deep___Transfer_Learning_for_Antimetabole_Detection.pdf"]}
{"year":"2023","title":"Detection and Mitigation of Gender Bias in Natural Language Processing","authors":["H Dawkins - 2023"],"snippet":"This thesis contributes to our collective understanding of how gender bias arises in natural language processing systems, provides new detection and measurement tools, and develops mitigation methods. More specifically, we quantify and reduce …","url":["https://atrium.lib.uoguelph.ca/xmlui/bitstream/handle/10214/27467/Dawkins_Hillary_202302_Phd.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"Detection of Privacy-Harming Social Media Posts in Italian","authors":["F Peiretti, RG Pensa - International Symposium on Security and Privacy in …, 2023"],"snippet":"As many psychological and sociological study reveal, many people disclose too much privacy-harming information in social media in the form of text and multimedia posts, thus exposing themselves and other persons to several security risks …","url":["https://www.researchgate.net/profile/Ruggero-Pensa/publication/372869652_Detection_of_Privacy-Harming_Social_Media_Posts_in_Italian/links/64cdff1540a524707b983e80/Detection-of-Privacy-Harming-Social-Media-Posts-in-Italian.pdf"]}
{"year":"2023","title":"Detection of Propagandistic Techniques in Text using Pretrained Language Models","authors":["K HUDCOVICOVÁ"],"snippet":"… mC4 consists of natural text in 101 languages extracted from the public Common Crawl web scrape. However, pre-trained generative multilingual language models can exhibit problematic behavior in the zero-shot setting. They may translate a …","url":["https://is.muni.cz/th/o7nqq/Propaganda_Detection.pdf"]}
{"year":"2023","title":"Detection of Truthful, Semi-Truthful, False and Other News with Arbitrary Topics Using BERT-Based Models","authors":["E Shushkevich, J Cardiff, A Boldyreva - 2023 33rd Conference of Open Innovations …, 2023"],"snippet":"Easy and uncontrolled access to the Internet provokes the wide propagation of false information, which freely circulates in the Internet. Researchers usually solve the problem of fake news detection (FND) in the framework of a known topic and binary …","url":["https://ieeexplore.ieee.org/abstract/document/10143004/"]}
{"year":"2023","title":"Determining sentiment views of verbal multiword expressions using linguistic features","authors":["M Wiegand, M Schulder, J Ruppenhofer - Natural Language Engineering, 2023"],"snippet":"We examine the binary classification of sentiment views for verbal multiword expressions (MWEs). Sentiment views denote the perspective of the holder of some opinion. We distinguish between MWEs conveying the view of the speaker of the …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/B992222E564C948CE90EA7238C0E9195/S1351324923000153a.pdf/determining-sentiment-views-of-verbal-multiword-expressions-using-linguistic-features.pdf"]}
{"year":"2023","title":"DeTexD: A Benchmark Dataset for Delicate Text Detection","authors":["A Chernodub, S Yavnyi, O Sliusarenko, J Razzaghi… - The 7th Workshop on Online …, 2023"],"snippet":"… For our DeTexD Benchmark dataset (Table 3), we extracted data from various websites in CommonCrawl5, where we specifically targeted news websites, forums discussing sensitive topics (eg, Mental Health Forum6, and able2know7 which …","url":["https://aclanthology.org/2023.woah-1.2.pdf"]}
{"year":"2023","title":"Developing a Flexible System for a Friendly Robot to Ease Dementia (FRED) Using Cloud Technologies and Software Design Patterns","authors":["RJ Bray - 2023"],"snippet":"In this work, we designed two prototypes for a friendly robot to ease dementia (FRED). This affordable social robot is designed to provide company to older adults with cognitive decline, create reminders for important events and tasks, like taking …","url":["https://trace.tennessee.edu/cgi/viewcontent.cgi?article=9197&context=utk_gradthes"]}
{"year":"2023","title":"Developing a Named Entity Recognition Dataset for Tagalog","authors":["LJV Miranda - arXiv preprint arXiv:2311.07161, 2023"],"snippet":"We present the development of a Named Entity Recognition (NER) dataset for Tagalog. This corpus helps fill the resource gap present in Philippine languages today, where NER resources are scarce. The texts were obtained from a pretraining …","url":["https://arxiv.org/pdf/2311.07161"]}
{"year":"2023","title":"Developing an Incivility Dictionary for German Online Discussions–a Semi-Automated Approach Combining Human and Artificial Knowledge","authors":["A Stoll, L Wilms, M Ziegele - Communication Methods and Measures, 2023"],"snippet":"… of Common Crawl and Wikipedia, consisting of over 67 billion tokens (Bojanowski et al., 2017; Grave et al., 2018). The common crawl project … In addition to common crawl, the German Wikipedia dump 15 was considered to train the embedding …","url":["https://www.tandfonline.com/doi/pdf/10.1080/19312458.2023.2166028"]}
{"year":"2023","title":"Developing Hybrid Model for Analyzing Sentiment of Textual Data for Amazon Product Reviews Using Deep Learning","authors":["MAM Ali, DRSN Lokhande, SAS Alshaibani - Harbin Gongcheng Daxue Xuebao …, 2023"],"snippet":"… Common Crawl and Wikipedia, has also contributed to the progress of NLP [8]. These resources enable researchers and practitioners to leverage transfer learning techniques, where models pre-trained on vast amounts of unlabeled text can be fine-tuned …","url":["https://harbinengineeringjournal.com/index.php/journal/article/download/651/484"]}
{"year":"2023","title":"Development of a web service for creating tests based on text analysis using natural language processing technologies","authors":["TA Vakaliuk, OV Chyzhmotria, SO Didkivska, I Linevych - International Journal of …, 2023"],"snippet":"… small in size, while the Common Crawl dataset (Common crawl) is huge and very diverse but has a relatively low quality. So, to satisfy all requirements, Google developed the Colossal Clean Crawled Corpus (C4), a cleaned version of Common …","url":["https://journals.us.edu.pl/index.php/IJREL/article/download/15762/12504"]}
{"year":"2023","title":"Diagnostic Accuracy of Differential-Diagnosis Lists Generated by Generative Pretrained Transformer 3 Chatbot for Clinical Vignettes with Common Chief Complaints …","authors":["T Hirosawa, Y Harada, M Yokose, T Sakamoto… - International Journal of …, 2023"],"snippet":"The diagnostic accuracy of differential diagnoses generated by artificial intelligence (AI) chatbots, including the generative pretrained transformer 3 (GPT-3) chatbot (ChatGPT-3) is unknown. This study evaluated the accuracy of differential-diagnosis lists …","url":["https://www.mdpi.com/2137560"]}
{"year":"2023","title":"Diagnostic and Management Performance of ChatGPT in Obstetrics and Gynecology","authors":["LAMMG Afrooz, MHSI Alkatoute - 2023"],"snippet":"… ChatGPT is one of the largest AI models, with over 175 billion model parameters and 570 gigabytes of training data from the “common crawl” dataset, which contains almost all unstructured text on the internet. The Common Crawl corpus constitutes …","url":["https://karger.com/goi/article-pdf/doi/10.1159/000533177/3979362/000533177.pdf"]}
{"year":"2023","title":"DIATOPIT: A Corpus of Social Media Posts for the Study of Diatopic Language Variation in Italy","authors":["A Ramponi, C Casula - Tenth Workshop on NLP for Similar Languages …, 2023"],"snippet":"We introduce DiatopIt, the first corpus specifically focused on diatopic language variation in Italy for language varieties other than Standard Italian. DiatopIt comprises over 15K geolocated social media posts from Twitter over a period of two …","url":["https://aclanthology.org/2023.vardial-1.19.pdf"]}
{"year":"2023","title":"Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models","authors":["M Meeus, S Jain, M Rei, YA de Montjoye - arXiv preprint arXiv:2310.15007, 2023"],"snippet":"… Finding members is typically easy as most LLMs today have seen sources such as Common Crawl [15] or Project Gutenberg [24]. Given … Data retrieved from the frequently updated Common Crawl [15] has for instance been the majority of the …","url":["https://arxiv.org/pdf/2310.15007"]}
{"year":"2023","title":"Digital humanities and web archives: Possible new paths for","authors":["N Brügger - International Journal"],"snippet":"This article discusses the importance of web archives making their collections available as data and not only as sources seen through the Wayback Machine’s interface where only individual web pages are displayed. This will help unlock the …","url":["https://pure.au.dk/portal/files/301137949/Digital_humanities_and_web_archives_Possible_new_paths_for_combining_datasets_Accepted_manuscript.pdf"]}
{"year":"2023","title":"DiLoCo: Distributed Low-Communication Training of Language Models","authors":["A Douillard, Q Feng, AA Rusu, R Chhaparia… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLM) have become a critical component in many applications of machine learning. However, standard approaches to training LLM require a large number of tightly interconnected accelerators, with devices …","url":["https://arxiv.org/pdf/2311.08105"]}
{"year":"2023","title":"Disambiguating Italian homographic heterophones with SoundChoice and testing ChatGPT as a data-generating tool","authors":["M Nanni - 2023"],"snippet":"Text-To-Speech systems are challenged by the presence of homographs, words that have more than one possible pronunciation. Rule-based approaches are often still the preferred solution to this issue in the industry. However, there have been …","url":["https://www.diva-portal.org/smash/get/diva2:1769395/FULLTEXT01.pdf"]}
{"year":"2023","title":"Disaster Tweets: Analysis from the Metaphor Perspective and Classification Using LLM's","authors":["T Alcántara, O García-Vázquez, H Calvo… - … International Conference on …, 2023"],"snippet":"Nowadays, social networks, specially Twitter (now X), allow the spread of information about all topics; since this platform is completely open, there is little to none restriction on what a user can post, hence, creating a lack of confidence and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47640-2_9"]}
{"year":"2023","title":"Discerning mental illnesses from social media posts using machine and deep learning algorithms","authors":["R Harish, A Vaid, SS Byakod, A Kumar, A Arya - AIP Conference Proceedings, 2023"],"snippet":"Deep learning has played a pivotal role in solving a wide array of problems. These powerful models can also be used for detecting mental illness. Knowing this in advance shall help individuals to utilize appropriate prophylactic measures and …","url":["https://pubs.aip.org/aip/acp/article/2745/1/020017/2901885"]}
{"year":"2023","title":"DISCO-10M: A Large-Scale Music Dataset","authors":["LA Lanzendörfer, F Grötschla, E Funke, R Wattenhofer - arXiv preprint arXiv …, 2023"],"snippet":"… In the field of text processing, datasets such as CommonCrawl [1] and the Pile [13] have made substantial amounts of written content available for training large language models. For instance, the Pile contains an extensive dataset of 825 …","url":["https://arxiv.org/pdf/2306.13512"]}
{"year":"2023","title":"Disco-Bench: A Discourse-Aware Evaluation Benchmark for Language Modelling","authors":["L Wang, Z Du, D Liu, C Deng, D Yu, H Jiang, Y Wang… - arXiv preprint arXiv …, 2023"],"snippet":"Modeling discourse -- the linguistic phenomena that go beyond individual sentences, is a fundamental yet challenging aspect of natural language processing (NLP). However, existing evaluation benchmarks primarily focus on the evaluation of inter-sentence …","url":["https://arxiv.org/pdf/2307.08074"]}
{"year":"2023","title":"Disentangling Transformer Language Models as Superposed Topic Models","authors":["J Lim, H Lauw - Proceedings of the 2023 Conference on Empirical …, 2023"],"snippet":"Topic Modelling is an established research area where the quality of a given topic is measured using coherence metrics. Often, we infer topics from Neural Topic Models (NTM) by interpreting their decoder weights, consisting of top-activated words projected …","url":["https://aclanthology.org/2023.emnlp-main.534.pdf"]}
{"year":"2023","title":"DistilGREEK-BERT: A distilled version of the GREEK-BERT model","authors":["EA Karavangeli, DA Pantazi, M Iliakis - 2023"],"snippet":"ABSTRACT Language Models for Natural Language Processing (NLP) have constituted subject of engagement and endless research for over two decades. All models, having been introduced through the years, have the tendency to increase in …","url":["https://pergamos.lib.uoa.gr/uoa/dl/object/3338746/file.pdf"]}
{"year":"2023","title":"Distilling semantic concept embeddings from contrastively fine-tuned language models","authors":["N Li, H Kteich, Z Bouraoui, S Schockaert - 2023"],"snippet":"Learning vectors that capture the meaning of concepts remains a fundamental challenge. Somewhat surprisingly, perhaps, pretrained language models have thus far only enabled modest improvements to the quality of such concept embeddings …","url":["https://orca.cardiff.ac.uk/id/eprint/159300/7/_SIGIR_2023__BERT_contrastive_properties-4.pdf"]}
{"year":"2023","title":"Distinguishing Romanized Hindi from Romanized Urdu","authors":["E Nielsen, C Kirov, B Roark - Proceedings of the Workshop on Computation and …, 2023"],"snippet":"We examine the task of distinguishing between Hindi and Urdu when those languages are romanized, ie, written in the Latin script. Both languages are widely informally romanized, and to the extent that they are identified in the Latin script by …","url":["https://aclanthology.org/2023.cawl-1.5.pdf"]}
{"year":"2023","title":"Distributed Marker Representation for Ambiguous Discourse Markers and Entangled Relations","authors":["D Ru, L Qiu, X Qiu, Y Zhang, Z Zhang - arXiv preprint arXiv:2306.10658, 2023"],"snippet":"Discourse analysis is an important task because it models intrinsic semantic structures between sentences in a document. Discourse markers are natural representations of discourse in our daily language. One challenge is that the …","url":["https://arxiv.org/pdf/2306.10658"]}
{"year":"2023","title":"Diverse Paraphrase Generation for Evaluating Model Robustness","authors":["D Verma - 2023"],"snippet":"… The BoW model consisted of GloVe (300 dimension embeddings trained on 840B CommonCrawl tokens) [49] vectors as the embedding layer. The average of all word vectors for the input sequence is treated as its final representation. The …","url":["https://search.proquest.com/openview/a7af10226e95a379cdc4b02c51ee293e/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection","authors":["Y Chen, Z Ding, X Chen, D Wagner - arXiv preprint arXiv:2304.00409, 2023"],"snippet":"We propose and release a new vulnerable source code dataset. We curate the dataset by crawling security issue websites, extracting vulnerability-fixing commits and source codes from the corresponding projects. Our new dataset contains 150 …","url":["https://arxiv.org/pdf/2304.00409"]}
{"year":"2023","title":"Diving into Deep Learning: On Reading and Interpreting Black Boxes","authors":["J Dobson - 2023"],"snippet":"The deep neural networks used in computer vision and in recent large language models are widely recognized as black boxes, a term that describes their complicated architectures and opaque decision-making mechanisms. This essay …","url":["https://www.researchsquare.com/article/rs-2643580/latest.pdf"]}
{"year":"2023","title":"DNS Dependencies as an Expression of the Digital Divide: the Example of Australia","authors":["N Nazemi, O Tavallaie, AY Zomaya, R Holz"],"snippet":"This paper investigates the relationship between the digital divide, Internet transparency, and DNS dependencies. The term “digital divide” refers to a gap between how different population groups can access and use digital technology …","url":["https://ralphholz.science/publications/DnsDependenciesAsAnExpressionOfTheDigitalDivideTheExampleOfAustralia.pdf"]}
{"year":"2023","title":"Do AIs dream of electric comics? Generative AI models, digital memory, and creativity","authors":["G Busi Rizzi - La memoria digitale. Forme del testo e organizzazione …, 2023"],"snippet":"… called LAION, that processes through a CLIP model image-text pairs obtained from another non-profit organization called Common CrawlCommon Crawl, in turn, gets its images by scraping billions of web pages monthly and releasing them as …","url":["https://biblio.ugent.be/publication/01H89X6FR6HNJ1HHH6BHFAS6EM/file/01H89XBMS7QTD4MH3YVXR6ADS8.pdf"]}
{"year":"2023","title":"Do large language models solve verbal analogies like children do?","authors":["CE Stevenson, M ter Veen, R Choenni… - arXiv preprint arXiv …, 2023"],"snippet":"Analogy-making lies at the heart of human cognition. Adults solve analogies such as \\textit{Horse belongs to stable like chicken belongs to ...?} by mapping relations (\\textit{kept in}) and answering \\textit{chicken coop}. In contrast, children often use association …","url":["https://arxiv.org/pdf/2310.20384"]}
{"year":"2023","title":"Do Localization Methods Actually Localize Memorized Data in LLMs?","authors":["TY Chang, J Thomason, R Jia - arXiv preprint arXiv:2311.09060, 2023"],"snippet":"Large language models (LLMs) can memorize many pretrained sequences verbatim. This paper studies if we can locate a small set of neurons in LLMs responsible for memorizing a given sequence. While the concept of localization is often mentioned …","url":["https://arxiv.org/pdf/2311.09060"]}
{"year":"2023","title":"Do Not Discard–Extracting Useful Fragments from Low-Quality Parallel Data to Improve Machine Translation","authors":["S Steingrímsson, P Lohar, H Loftsson, A Way - CoCo4MT 2023, 2023"],"snippet":"When parallel corpora are preprocessed for machine translation (MT) training, a part of the parallel data is commonly discarded and deemed non-parallel due to odd-length ratio, overlapping text in source and target sentences or failing some other form of a …","url":["https://files.sciconf.cn/upload/file/20230903/20230903151747_19845.pdf#page=13"]}
{"year":"2023","title":"DocEdit: Language-Guided Document Editing","authors":["P Mathur, R Jain, J Gu, F Dernoncourt, D Manocha… - Proceedings of the AAAI …, 2023"],"snippet":"Professional document editing tools require a certain level of expertise to perform complex edit operations. To make editing tools accessible to increasingly novice users, we investigate intelligent document assistant systems that can make or …","url":["https://ojs.aaai.org/index.php/AAAI/article/download/25282/25054"]}
{"year":"2023","title":"Document Entity Retrieval with Massive and Noisy Pre-training","authors":["L Yu, J Miao, X Sun, J Chen, AG Hauptmann, H Dai… - arXiv preprint arXiv …, 2023"],"snippet":"Visually-Rich Document Entity Retrieval (VDER) is a type of machine learning task that aims at recovering text spans in the documents for each of the entities in question. VDER has gained significant attention in recent years thanks to its broad …","url":["https://arxiv.org/pdf/2306.08937"]}
{"year":"2023","title":"DOES CLIP'S GENERALIZATION PERFORMANCE MAINLY STEM FROM HIGH TRAIN-TEST SIMILARITY?","authors":["P Mayilvahanan, T Wiedemer, E Rusak, M Bethge… - arXiv preprint arXiv …, 2023"],"snippet":"… In comparison, LAION-400M comprises roughly 400 million samples scraped from the Common Crawl dataset*. The Common Crawl dataset comprises petabytes of data collected over more than a decade of web crawling; LAION-400M, therefore …","url":["https://arxiv.org/pdf/2310.09562"]}
{"year":"2023","title":"Does fine-tuning GPT-3 with the OpenAI API leak personally-identifiable information?","authors":["AY Sun, E Zemour, A Saxena, U Vaidyanathan, E Lin… - arXiv preprint arXiv …, 2023"],"snippet":"… For these half of these generations, we use prompts from randomly select strings with character length 100 from an English-only subset of Common Crawl to serve as naive prompts to probe our model, inspired by the naive prompting strategy used by (Diera …","url":["https://arxiv.org/pdf/2307.16382"]}
{"year":"2023","title":"Does GPT-3 qualify as a co-author of a scientific paper publishable in peer-review journals according to the ICMJE criteria? A case study","authors":["A Osmanovic-Thunström, S Steingrimsson - Discover Artificial Intelligence, 2023"],"snippet":"This paper explores the potential for a system to be a co-author on an academic paper based on the criteria proposed by the International Committee of Medical Journal Editors (ICMJE). We used a third generation generative pretrained …","url":["https://link.springer.com/article/10.1007/s44163-023-00055-7"]}
{"year":"2023","title":"Does GPT-3 qualify as a co-author of a scientific paper publishable in peer-review journals according to the ICMJE criteria?-A Case Study.","authors":["AO Thunström, S Steingrimsson - 2022"],"snippet":"This paper explores the potential for a system to be a co-author on an academic paper based on the criteria proposed by the International Committee of Medical Journal Editors (ICMJE). We used a third generation generative pretrained …","url":["https://www.researchsquare.com/article/rs-2404314/latest.pdf"]}
{"year":"2023","title":"Does Masked Language Model Pre-training with Artificial Data Improve Low-resource Neural Machine Translation?","authors":["H Tamura, T Hirasawa, H Kim, M Komachi - Findings of the Association for …, 2023"],"snippet":"Pre-training masked language models (MLMs) with artificial data has been proven beneficial for several natural language processing tasks such as natural language understanding and summarization; however, it has been less explored for neural …","url":["https://aclanthology.org/2023.findings-eacl.166.pdf"]}
{"year":"2023","title":"Does the first letter of one's name affect life decisions? A natural language processing examination of nominative determinism.","authors":["P Chatterjee, H Mishra, A Mishra - Journal of Personality and Social Psychology, 2023"],"snippet":"… That is, when running the analysis using the Common Crawl corpus, we obtained the embedding of person name, profession name, and city name from the Common Crawl corpus. This helped us test for nominative determinism using the millions of co-occurrences …","url":["https://psycnet.apa.org/record/2023-75670-001"]}
{"year":"2023","title":"DoGE: Domain Reweighting with Generalization Estimation","authors":["S Fan, M Pagliardini, M Jaggi - arXiv preprint arXiv:2310.15393, 2023"],"snippet":"… We see how DOGE seem to upweights significantly the common-crawl (cc) domain. In (b) we show DOGE domain weights for out-of-domain generalization. Those domain weights obtained by training on various training mixtures consisting …","url":["https://arxiv.org/pdf/2310.15393"]}
{"year":"2023","title":"Dolphin: A Challenging and Diverse Benchmark for Arabic NLG","authors":["EMB Nagoudi, A El-Shangiti, AR Elmadany… - arXiv preprint arXiv …, 2023"],"snippet":"We present Dolphin, a novel benchmark that addresses the need for an evaluation framework for the wide collection of Arabic languages and varieties. The proposed benchmark encompasses a broad range of 13 different NLG tasks, including text …","url":["https://arxiv.org/pdf/2305.14989"]}
{"year":"2023","title":"Don't Just Clean It, Proxy Clean It: Mitigating Bias by Proxy in Pre-Trained Models","authors":["S Panda, A Kobren, M Wick, Q Shen - Findings of the Association for Computational …, 2022"],"snippet":"Transformer-based pre-trained models are known to encode societal biases not only in their contextual representations, but also in downstream predictions when fine-tuned on task-specific data. We present D-Bias, an approach that selectively eliminates …","url":["https://aclanthology.org/2022.findings-emnlp.372.pdf"]}
{"year":"2023","title":"Don't Worry Accountants, ChatGPT Won't Be Taking Your Job... Yet","authors":["S Taylor, V Keselj"],"snippet":"ChatGPT has demonstrated the ability to generate plausible human-like text and research is underway to evaluate and benchmark its current performance in various domains. The research we present here provides a preliminary benchmark on …","url":["https://web.cs.dal.ca/~vlado/papers/cai23s.pdf"]}
{"year":"2023","title":"DONOTTRAIN: A Metadata Standard for Indicating Consent for Machine Learning","authors":["D Ippolito, YW Yu"],"snippet":"… take the Common Crawl, a publicly available crawl of the internet, as their starting point, and filter and process it into a training dataset. The Common Crawl currently respects robots.txt. For the learners.txt protocol to be useful, we would work with the Common …","url":["https://genlaw.github.io/CameraReady/42.pdf"]}
{"year":"2023","title":"DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining","authors":["SM Xie, H Pham, X Dong, N Du, H Liu, Y Lu, P Liang… - arXiv preprint arXiv …, 2023"],"snippet":"The mixture proportions of pretraining data domains (eg, Wikipedia, books, web text) greatly affect language model (LM) performance. In this paper, we propose Domain Reweighting with Minimax Optimization (DoReMi), which first trains a small proxy …","url":["https://arxiv.org/pdf/2305.10429"]}
{"year":"2023","title":"Dr ChatGPT tell me what I want to hear: How different prompts impact health answer correctness","authors":["B Koopman, G Zuccon"],"snippet":"This paper investigates the significant impact different prompts have on the behaviour of ChatGPT when used for health information seeking. As people more and more depend on generative large language models (LLMs) like ChatGPT, it is …","url":["https://ielab.io/files/emnlp2023-healthgpt.pdf"]}
{"year":"2023","title":"Dr ChatGPT, tell me what I want to hear: How prompt knowledge impacts health answer correctness","authors":["G Zuccon, B Koopman - arXiv preprint arXiv:2302.13793, 2023"],"snippet":"… The actual documents are web pages from the noclean version of the C4 dataset: ≈1B English text extracts from the April 2019 snapshot of Common Crawl. Some passages are long and exceed the maximum token limit of ChatGPT. We trimmed …","url":["https://arxiv.org/pdf/2302.13793"]}
{"year":"2023","title":"Dream the Impossible: Outlier Imagination with Diffusion Models","authors":["X Du, Y Sun, X Zhu, Y Li - arXiv preprint arXiv:2309.13415, 2023"],"snippet":"… The model was trained on 5 billion pairs of images and captions taken from LAION-5B [87], a publicly available dataset derived from Common Crawl data scraped from the web. Given a class name y, the generation process can be mathematically denoted …","url":["https://arxiv.org/pdf/2309.13415"]}
{"year":"2023","title":"DreamShot: Teaching Cinema Shots to Latent Diffusion Models","authors":["T Cerquitelli, B Vacchetti, T Massaglia - 2023"],"snippet":"This thesis work presents a comprehensive overview of recent advancements in image synthesis models, exploring the recent developments of Diffusion Models [1] and their finetuning. The primary contribution consists in a novel approach that …","url":["https://webthesis.biblio.polito.it/27718/1/tesi.pdf"]}
{"year":"2023","title":"Dynamic Masking Rate Schedules for MLM Pretraining","authors":["Z Ankner, N Saphra, D Blalock, J Frankle, ML Leavitt - arXiv preprint arXiv …, 2023"],"snippet":"Most works on transformers trained with the Masked Language Modeling (MLM) objective use the original BERT model's fixed masking rate of 15%. Our work instead dynamically schedules the masking ratio throughout training. We found that linearly …","url":["https://arxiv.org/pdf/2305.15096"]}
{"year":"2023","title":"Dzongkha to English translation using the neural machine translation approach","authors":["K Wangchuk, SC Navaneethakrishnan, Y Jamtsho… - Indonesian Journal of …, 2023"],"snippet":"… The word embeddings were trained using the continuous bag of words (CBOW) model on common crawl and Wikipedia. Word vectors were trained using CBOW with position-weights, embedding dimension of 300, ngram characters of length five …","url":["https://www.researchgate.net/profile/Karma-Wangchuk/publication/371685952_Dzongkha_to_English_translation_using_the_neural_machine_translation_approach/links/649d87ccc41fb852dd3e5ddf/Dzongkha-to-English-translation-using-the-neural-machine-translation-approach.pdf"]}
{"year":"2023","title":"EcomGPT-CT: Continual Pre-training of E-commerce Large Language Models with Semi-structured Data","authors":["S Ma, S Huang, S Huang, X Wang, Y Li, HT Zheng… - arXiv preprint arXiv …, 2023"],"snippet":"… Generally, commonly used data for LLM pretraining is obtained from organized long text on web pages, such as CommonCrawl and Wikipedia. However, in some specific domains including ecommerce domain, a substantial amount of text data is …","url":["https://arxiv.org/pdf/2312.15696"]}
{"year":"2023","title":"Ecosystem Graphs: The Social Footprint of Foundation Models","authors":["R Bommasani, D Soylu, TI Liao, KA Creel, P Liang - arXiv preprint arXiv:2303.15772, 2023"],"snippet":"Foundation models (eg ChatGPT, StableDiffusion) pervasively influence society, warranting immediate social attention. While the models themselves garner much attention, to accurately characterize their impact, we must consider the broader …","url":["https://arxiv.org/pdf/2303.15772"]}
{"year":"2023","title":"EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture","authors":["A Petrescu, CO Truică, ES Apostol, A Paschke - arXiv preprint arXiv:2301.12805, 2023"],"snippet":"… The additional data included CommonCrawl News dataset (63 million articles, 76 GB), Web text corpus (38 GB), and Stories from Common Crawl (31 GB). This coupled with a whopping 1024 V100 Tesla GPUs running for a day, led to pre-training …","url":["https://arxiv.org/pdf/2301.12805"]}
{"year":"2023","title":"Educational data augmentation in physics education research using ChatGPT","authors":["F Kieser, P Wulff, J Kuhn, S Küchemann - arXiv preprint arXiv:2307.14475, 2023"],"snippet":"… [22] Early LLM were trained based on large text corpora such as the Common Crawl (ie, dump of the Internet, 60%[23]), WebText2 (22%), or Wikipedia (3%) with the training objective to predict next words in a sequence (a sort of Cloze test, [18]) …","url":["https://arxiv.org/pdf/2307.14475"]}
{"year":"2023","title":"Effective Long-Context Scaling of Foundation Models","authors":["W Xiong, J Liu, I Molybog, H Zhang, P Bhargava… - arXiv preprint arXiv …, 2023"],"snippet":"We present a series of long-context LLMs that support effective context windows of up to 32,768 tokens. Our model series are built through continual pretraining from Llama 2 with longer training sequences and on a dataset where long texts are …","url":["https://arxiv.org/pdf/2309.16039"]}
{"year":"2023","title":"Effects of paraphrasing and demographic metadata on NLI classification performance","authors":["M Marx Larre - 2023"],"snippet":"… It is a neural network that has been pre-trained on a large dataset of texts made up from a filtered version of CommonCrawl, WebText2, Books1, Books2 (two internet-based books corpora) and Wikipedia. GPT-3 can generate human-like text in a variety of …","url":["https://elib.uni-stuttgart.de/bitstream/11682/13674/1/Thesis_MiguelMarxLarre.pdf"]}
{"year":"2023","title":"Efficient Approximate Nearest Neighbor Search in Multi-dimensional Databases","authors":["YUN PENG, B CHOI, T CHAN, J YANG, J XU - 2023"],"snippet":"Approximate nearest neighbor (ANN) search in multi-dimensional databases is a fundamental search and has many applications, such as image retrieval [28, 44], recommendation [12], entity resolution [21], and sequence matching [10]. Many ANN …","url":["https://www.comp.hkbu.edu.hk/~edisonchan/publication/tau-MNG.pdf"]}
{"year":"2023","title":"Efficient Continual Pre-training for Building Domain Specific Large Language Models","authors":["Y Xie, K Aggarwal, A Ahmad - arXiv preprint arXiv:2311.08545, 2023"],"snippet":"… We use two sources of data for the financial corpus: the financial news common crawl and SEC filings. Financial News CommonCrawl is curated by filtering out financial news from the public CommonCrawl data. We follow the de-duplication …","url":["https://arxiv.org/pdf/2311.08545"]}
{"year":"2023","title":"Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning","authors":["M Ostendorff, G Rehm - arXiv preprint arXiv:2301.09626, 2023"],"snippet":"Most Transformer language models are primarily pretrained on English text, limiting their use for other languages. As the model sizes grow, the performance gap between English and other languages with fewer compute and data resources …","url":["https://arxiv.org/pdf/2301.09626"]}
{"year":"2023","title":"Efficient Phishing Detection and Prevention Using Support Vector Machine (SVM) Algorithm","authors":["M Arivukarasi, A Manju, R Kaladevi, S Hariharan… - 2023 IEEE 12th …, 2023"],"snippet":"Phishing issues influence the electronic trade in light of the fact that web-based clients trust the Internet climate less. Phishers use procedures that advance to bait online clients, making new phishing sites and spreading messages that attempt to …","url":["https://ieeexplore.ieee.org/abstract/document/10134735/"]}
{"year":"2023","title":"Efficient Pre-training for Localized Instruction Generation of Videos","authors":["A Batra, D Moltisanti, L Sevilla-Lara, M Rohrbach… - arXiv preprint arXiv …, 2023"],"snippet":"Procedural videos show step-by-step demonstrations of tasks like recipe preparation. Understanding such videos is challenging, involving the precise localization of steps and the generation of textual instructions. Manually annotating steps and writing …","url":["https://arxiv.org/pdf/2311.15964"]}
{"year":"2023","title":"Efficient, Adaptable and Interpretable NLP","authors":["N Rethmeier"],"snippet":"In natural language processing (NLP), a central concern is how to develop and evaluate language model pretraining that better transfers and adapts to downstream tasks. Due to their black box character, it is hard to understand how models transfers …","url":["https://di.ku.dk/english/research/phd/phd-theses/2023/PhD_Thesis_Nils_Rethmeier.pdf"]}
{"year":"2023","title":"Efficiently Adapting Pretrained Language Models To New Languages","authors":["Z Csaki, P Pawakapan, U Thakker, Q Xu - arXiv preprint arXiv:2311.05741, 2023"],"snippet":"… For the Thai pre-training corpus, we combine the Thai subsets of OSCAR [41], MC4 [42], and CCNet [43], which are all derived from Common Crawl. The entire combined corpus was processed with MinHash deduplication [44, 45] with 1-grams …","url":["https://arxiv.org/pdf/2311.05741"]}
{"year":"2023","title":"Einsatzbereiche semantisch strukturierter Daten bei der Unternehmensanalyse","authors":["J Gruemmer - 2023"],"snippet":"This dissertation consists of 6 papers. The papers investigate the areas of application of semantically structured data in company analysis. The first paper examines the extent to which alternative data can support tax audits. It is also …","url":["https://opus4.kobv.de/opus4-fau/files/22361/20230209_JG_Dissertation.pdf"]}
{"year":"2023","title":"Email Spam Detection Using Multi-head CNN-BiGRU Network","authors":["A Gupta, J Patil, S Soni, A Rajan - … , ANTIC 2022, Varanasi, India, December 22–24 …, 2023"],"snippet":"Spam emails refer to unsolicited email messages, usually sent in bulk to a large list of recipients with the purpose of marketing, or luring individuals to download malware or click on phishing links. Although much research has been done on this …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28180-8_3"]}
{"year":"2023","title":"Embedded Lexica","authors":["PJ Chester - 2023"],"snippet":"Researchers oftentimes find themselves in positions where they need to extract information, such as events or target topics, from large corpora. One common solution involves applying semantically-related keywords to identify tweets, news …","url":["https://patrickjchester.com/publication/chprop3/chprop3.pdf"]}
{"year":"2023","title":"EMit at EVALITA 2023: Overview of the Categorical Emotion Detection in Italian Social Media Task","authors":["O Araque, S Frenda, R Sprugnoli, D Nozza, V Patti - Proceedings of the Eighth …, 2023"],"snippet":"The Emotions in Italian (EMit) task is the first edition of a shared task on emotion analysis and opinion mining in Italian messages at EVALITA 2023. EMit presents two subtasks:(i) Subtask A, that consists in an emotion detection challenge, and (ii) …","url":["https://ceur-ws.org/Vol-3473/paper1.pdf"]}
{"year":"2023","title":"EMMA-X: An EM-like Multilingual Pre-training Algorithm for Cross-lingual Representation Learning","authors":["P Guo, X Wei, Y Hu, B Yang, D Liu, F Huang, J Xie - arXiv preprint arXiv:2310.17233, 2023"],"snippet":"Expressing universal semantics common to all languages is helpful in understanding the meanings of complex and culture-specific sentences. The research theme underlying this scenario focuses on learning universal …","url":["https://arxiv.org/pdf/2310.17233"]}
{"year":"2023","title":"Emotion Hunters at EMit: Categorical Emotion Detection combining BERT and ChatGPT models","authors":["G Calò, F Massafra, B De Carolis, C Loglisci - 2023"],"snippet":"Emotion detection in text plays a crucial role in various applications, such as customer feedback analysis, social media monitoring, or for the analysis of the verbal part of human communication. Deep learning techniques have shown …","url":["https://ceur-ws.org/Vol-3473/paper2.pdf"]}
{"year":"2023","title":"Emotion recognition in italian political language for prefiguring crisis in the balance of the parties' coalitions","authors":["A Forciniti, E Zavarrone, M Paolillo - Quality & Quantity, 2023"],"snippet":"The purpose of this study is to describe the emotions that dominated the political vocabulary used on Twitter during the Covid-19 epidemic by the leaders of the major Italian political parties, including Forza Italia, Movimento 5 Stelle, Fratelli d’Italia …","url":["https://link.springer.com/article/10.1007/s11135-023-01729-1"]}
{"year":"2023","title":"Empirical Analysis of Beam Search Curse and Search Errors with Model Errors in Neural Machine Translation","authors":["J He, S Sun, X Jia, W Li - Proceedings of the 24th Annual Conference of the …, 2023"],"snippet":"Beam search is the most popular decoding method for Neural Machine Translation (NMT) and is still a strong baseline compared with the newly proposed sampling-based methods. To better understand beam search, we investigate its two well-recognized …","url":["https://aclanthology.org/2023.eamt-1.10.pdf"]}
{"year":"2023","title":"Empirical evaluation of Uncertainty Quantification in Retrieval-Augmented Language Models for Science","authors":["S Wagle, S Munikoti, A Acharya, S Smith… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs) have shown remarkable achievements in natural language processing tasks, producing high-quality outputs. However, LLMs still exhibit limitations, including the generation of factually incorrect information. In safety-critical …","url":["https://arxiv.org/pdf/2311.09358"]}
{"year":"2023","title":"Empirical study of pretrained multilingual language models for zero-shot cross-lingual generation","authors":["N Chirkova, S Liang, V Nikoulina - arXiv preprint arXiv:2310.09917, 2023"],"snippet":"Zero-shot cross-lingual generation assumes finetuning the multilingual pretrained language model (mPLM) on a generation task in one language and then using it to make predictions for this task in other languages. Previous works notice a frequent …","url":["https://arxiv.org/pdf/2310.09917"]}
{"year":"2023","title":"Empowering Short Answer Grading: Integrating Transformer-Based Embeddings and BI-LSTM Network","authors":["WH Gomaa, AE Nagib, MM Saeed, A Algarni, E Nabil - Big Data and Cognitive …, 2023"],"snippet":"… The T5 model was trained on the 700 GB Colossal Clean Crawled Corpus dataset, a cleaned version of the Common Crawl dataset that included only English text. It achieved state-of-the-art performance on several NLP benchmarks and could be …","url":["https://www.mdpi.com/2504-2289/7/3/122"]}
{"year":"2023","title":"Enabling Cross-lingual Information Retrieval for African Languages","authors":["O Ogundepo - 2023"],"snippet":"… Another common approach is to exploit existing large multilingual corpora, eg, the Common Crawl5 and Wikipedia. For example, the HC4 corpus for cross-lingual information retrieval was created from Common Crawl data [30]. Examples of …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19361/Ogundepo_Odunayo.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"Encoding the Enemy: The Politics Within and Around Ethical Algorithmic War","authors":["J Moses, G Ford - Global Society, 2023"],"snippet":"This article develops a critique of the politics of algorithmic war and autonomous weapons systems. While much of the existing debate is focused on whether algorithmic weapons technologies can satisfy the ethics and laws of war, we argue …","url":["https://www.tandfonline.com/doi/full/10.1080/13600826.2023.2234395"]}
{"year":"2023","title":"End-to-End Speech-to-Text Translation: A Survey","authors":["N Sethiya, CK Maurya - arXiv preprint arXiv:2312.01053, 2023"],"snippet":"… Finally, a language model (LM) is trained on CommonCrawl data and combined with the ST model to generate text via beam-search decoding. Following along, for training E2E model, (Wang et al., 2021b) produces pseudo-labels by cascading ASR …","url":["https://arxiv.org/pdf/2312.01053"]}
{"year":"2023","title":"Energy Estimates Across Layers of Computing: From Devices to Large-Scale Applications in Machine Learning for Natural Language Processing, Scientific …","authors":["S Shankar - arXiv preprint arXiv:2310.07516, 2023"],"snippet":"… These AI/ML methods depend on training on a large corpus, namely significant amounts of data using words, phrases, part-of speech requirements, existing collections of text from academic journals, books, social network websites, Wikipedia …","url":["https://arxiv.org/pdf/2310.07516"]}
{"year":"2023","title":"Engineering a Distributed-Memory Triangle Counting Algorithm","authors":["P Sanders, TN Uhl - arXiv preprint arXiv:2302.11443, 2023"],"snippet":"Counting triangles in a graph and incident to each vertex is a fundamental and frequently considered task of graph analysis. We consider how to efficiently do this for huge graphs using massively parallel distributed-memory machines …","url":["https://arxiv.org/pdf/2302.11443"]}
{"year":"2023","title":"Engineering the Best In-Context Input for GPT-3 in the OpenQA Task","authors":["K Huang, G Sullan, O Ebhomielen"],"snippet":"GPT-3, since its release, has garnered the attention of the NLP community due to its versatility across a wide range of NLP tasks. In this work, we use GPT-3 to approach the OpenQA task, where the model needs to answer input questions without being …","url":["https://kailihuang.com/assets/pdf/cs224u.pdf"]}
{"year":"2023","title":"Enhanced Emotion and Sentiment Recognition for Empathetic Dialogue System Using Big Data and Deep Learning Methods","authors":["M Kozłowski, K Gabor-Siatkowska, I Stefaniak… - International Conference on …, 2023","M Sowański, A Janicki"],"snippet":"… The process of using the Common Crawl web archive to create an enlarged corpus, named CORTEX+ pCC, is presented. An empathetic dialogue system named Terabot, incorporating the elaborated method, is also described. The system …","url":["https://link.springer.com/chapter/10.1007/978-3-031-35995-8_33","https://www.iccs-meeting.org/archive/iccs2023/papers/140730475.pdf"]}
{"year":"2023","title":"Enhanced Phishing URL Detection Using Leveraging BERT with Additional URL Feature Extraction","authors":["KS Jishnu, B Arthi - 2023 5th International Conference on Inventive …, 2023"],"snippet":"… Their heuristic-based deep learning technique made use of RNN models and datasets including PhishTank, Alexa, and Common Crawl. … Their research used the PhishTank and Common Crawl databases, which contain legal and phishing …","url":["https://ieeexplore.ieee.org/abstract/document/10220647/"]}
{"year":"2023","title":"Enhancing Customer Support with Knowledge Graph-Based Question Answering","authors":["N Stampe - 2023"],"snippet":"Many companies don’t utilize the huge amount of unstructured data they possess. Old issue tickets are one example. A company that possesses a lot of old issue tickets are Stibo Systems. Meanwhile, customer support staff receive issues that has …","url":["https://www.stiboaccelerator.com/s/Master_Thesis_Niels_Stampe_201708197.pdf"]}
{"year":"2023","title":"Enhancing EFL reading and writing through AI-powered tools: design, implementation, and evaluation of an online course","authors":["JC Hsiao, JS Chang - Interactive Learning Environments, 2023"],"snippet":"During the Covid-19 pandemic, global teachers gained extensive experiences with teaching online courses. To design quality online courses in the post-pandemic era, the impact of the latest technology, such as artificial intelligence (AI), must be …","url":["https://www.tandfonline.com/doi/abs/10.1080/10494820.2023.2207187"]}
{"year":"2023","title":"Enhancing Neural Text Detector Robustness with µAttacking and RR-Training. Electronics 2023, 12, 1948","authors":["G Liang, J Guerrero, F Zheng, I Alsmadi - 2023"],"snippet":"With advanced neural network techniques, language models can generate content that looks genuinely created by humans. Such advanced progress benefits society in numerous ways. However, it may also bring us threats that we have not seen …","url":["https://www.academia.edu/download/102918903/pdf.pdf"]}
{"year":"2023","title":"Enhancing RDF Verbalization with Descriptive and Relational Knowledge","authors":["F Zhang, M Zhang, S Liu, Y Sun, N Duan - ACM Transactions on Asian and Low …, 2023"],"snippet":"… T5 is pre-trained on a large and clean unlabeled text dataset named C4 from Common Crawl (about 750 GB) and achieves state-of-the-art performance on various benchmarks such as CNN/Daily Mail [4] and SuperGLUE [33]. T5 has ive …","url":["https://dl.acm.org/doi/pdf/10.1145/3595293"]}
{"year":"2023","title":"Enhancing Search Engine Results: A Comparative Study of Graph and Timeline Visualizations for Semantic and Temporal Relationship Discovery","authors":["MS Qureshi - 2023"],"snippet":"… Examples of open source data sets for search engine data are Common Crawl (CC) 10 which provides a large-scale data set of the crawled web, providing easy access to such data which is typically not made available for commercial search engines …","url":["https://search.proquest.com/openview/31cf7b284117b060a924c3a56299d09f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Enhancing Speaker Diarization with Large Language Models: A Contextual Beam Search Approach","authors":["TJ Park, K Dhawan, N Koluguri, J Balam - arXiv preprint arXiv:2309.05248, 2023"],"snippet":"Large language models (LLMs) have shown great promise for capturing contextual information in natural language processing tasks. We propose a novel approach to speaker diarization that incorporates the prowess of LLMs to exploit contextual cues …","url":["https://arxiv.org/pdf/2309.05248"]}
{"year":"2023","title":"Enhancing Text Summarization for Indian Languages: Mono, Multi and Cross-lingual Approaches","authors":["A URLANA - 2023"],"snippet":"The internet serves as a vast repository of information covering a diverse array of topics, ranging from blogs and articles to websites. However, it is important to note that not all of this information is valuable or relevant. Navigating through the plethora …","url":["https://www.researchgate.net/profile/Ashok-Urlana-2/publication/373989668_Enhancing_Text_Summarization_for_Indian_Languages_Mono_Multi_and_Cross-lingual_Approaches/links/65072d6e0142892697247d46/Enhancing-Text-Summarization-for-Indian-Languages-Mono-Multi-and-Cross-lingual-Approaches.pdf"]}
{"year":"2023","title":"Enhancing Traceability Link Recovery with Fine-Grained Query Expansion Analysis","authors":["T Peng, K She, Y Shen, X Xu, Y Yu - Information, 2023"],"snippet":"… The training datasets were Wikipedia and CommonCrawl datasets [16], which contain texts from various domains. Using common domain datasets for training enabled the model to better represent different software terminologies and vocabularies. …","url":["https://www.mdpi.com/2078-2489/14/5/270"]}
{"year":"2023","title":"EnML: Multi-label Ensemble Learning for Urdu Text Classification","authors":["F Mehmood, R Shahzadi, H Ghafoor, MN Asim… - ACM Transactions on Asian …, 2023"],"snippet":"… Crawl News Dataset (63 million articles, 76 GB), Web text corpus (38 GB), and Stories from Common Crawl were among the supplementary data (31 GB). We have utilized RoBERTa-Large-Multilingual with 12 attention heads and 12 hidden layers …","url":["https://dl.acm.org/doi/pdf/10.1145/3616111"]}
{"year":"2023","title":"ENTITY LINKING IN LOW-ANNOTATION DATA SETTINGS","authors":["E Schumacher - 2022"],"snippet":"… While these LMs were originally trained on standard NLP domain texts such as Wikipedia and CommonCrawl, the unsupervised nature of their training means that models tailored to specific domains can be produced. This is especially useful in the …","url":["https://www.cs.jhu.edu/~mdredze/publications/elliot_schumacher_thesis.pdf"]}
{"year":"2023","title":"Entity Matching using Large Language Models","authors":["R Peeters, C Bizer - arXiv preprint arXiv:2310.11244, 2023"],"snippet":"… The benchmark was built by extracting schema.org data from the Common Crawl We use the most difficult version of the benchmark including 80% corner-cases (hard positives and hard negatives) and use the following attributes: brand, title, currency …","url":["https://arxiv.org/pdf/2310.11244"]}
{"year":"2023","title":"ERATE: Efficient Retrieval Augmented Text Embeddings","authors":["V Raina, N Kassner, K Popat, P Lewis, N Cancedda… - The Fourth Workshop on …, 2023"],"snippet":"… An additional 100 million sentences sampled from common crawl (CC)5 are included in an expanded datastore to investigate the impact of increasing the datastore size. Table 1 details the statistics for each of these subsets. Sentences …","url":["https://aclanthology.org/2023.insights-1.2.pdf"]}
{"year":"2023","title":"Escaping the sentence-level paradigm in machine translation","authors":["M Post, M Junczys-Dowmunt - arXiv preprint arXiv:2304.12959, 2023"],"snippet":"It is well-known that document context is vital for resolving a range of translation ambiguities, and in fact the document setting is the most natural setting for nearly all translation. It is therefore unfortunate that machine translation -- both research and …","url":["https://arxiv.org/pdf/2304.12959"]}
{"year":"2023","title":"Essays in Environmental Economics","authors":["X Du - 2023"],"snippet":"This dissertation consists of three essays in the field of environmental economics. The first chapter provides the first causal evidence that hostile activities online lead to physical violence. Given the recently documented relationship between pollution …","url":["https://search.proquest.com/openview/8df778615d87a395701f3e18f35ed1a3/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Establishing An Optimal Online Phishing Detection Method: Evaluating Topological NLP Transformers on Text Message Data","authors":["H Milner, M Baron - Journal of Data Science and Intelligent Systems, 2023"],"snippet":"This research establishes an optimal classification model for online SMS spam detection by utilizing topological sentence transformer methodologies. The study is a response to the increasing sophisticated and disruptive activities of malicious actors …","url":["http://ojs.bonviewpress.com/index.php/jdsis/article/download/1131/568"]}
{"year":"2023","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","authors":["Y Li - arXiv preprint arXiv:2309.10677, 2023"],"snippet":"… For example, if the model M was trained on a Common Crawl dataset spanning 2016-2019, we would gather web pages specifically from this period. Similarly, if the model was trained on a 2019 dump of Wikipedia, we would collect articles from …","url":["https://arxiv.org/pdf/2309.10677"]}
{"year":"2023","title":"Ethical challenges of large language models-a systematic literature review","authors":["A Laakso - 2023"],"snippet":"… Current LLMs are by and large trained on massive datasets collected from the internet often the Common Crawl -material, a collection of vast amounts of internet content [S111]. However, just because private data is available online does not …","url":["https://helda.helsinki.fi/server/api/core/bitstreams/e507d025-8c84-4789-a043-f185fa51eb0a/content"]}
{"year":"2023","title":"Evading Text Based Emotion Detection Mechanism via Adversarial Attacks","authors":["A Bajaj, DK Vishwakarma - Neurocomputing, 2023"],"snippet":"Textual Emotion Analysis (TEA) seeks to extract and assess the emotional states of users from the text. Various Deep Learning (DL) algorithms have emerged rapidly and demonstrated success in numerous disciplines, including audio, image, and …","url":["https://www.sciencedirect.com/science/article/pii/S0925231223009104"]}
{"year":"2023","title":"Evaluating Biased Attitude Associations of Language Models in an Intersectional Context","authors":["SO Sabbaghi, R Wolfe, A Caliskan - arXiv preprint arXiv:2307.03360, 2023"],"snippet":"… Models trained on the Pile have been shown to outperform models trained on both raw and filtered versions of the Common Crawl on many benchmarks and downstream evaluations [23]. Prior work finds that GPT-Neo most strongly encodes …","url":["https://arxiv.org/pdf/2307.03360"]}
{"year":"2023","title":"Evaluating Cross Lingual Transfer for Morphological Analysis: a Case Study of Indian Languages","authors":["S Pawar, P Bhattacharyya, P Talukdar - … of the 20th SIGMORPHON workshop on …, 2023"],"snippet":"… It is pre-trained on the Common Crawl-based dataset and covers 101 languages. It is an encoder-decoder sequence generation model, unlike mBERT, which is an encoder-only multilingual model. Our task of root word extraction requires the …","url":["https://aclanthology.org/2023.sigmorphon-1.3.pdf"]}
{"year":"2023","title":"Evaluating Event Embeddings on Commodity Future Prices","authors":["B Steel, D Ruths - 2023"],"snippet":"… We developed a library for pulling and filtering websites from the Common Crawl Index, accessible here: github.com/networkdynamics/seldonite. We pulled Reuters news articles from Common Crawl from 2006 to 2021. We only keep articles that are …","url":["https://www.researchsquare.com/article/rs-3457976/latest.pdf"]}
{"year":"2023","title":"Evaluating Gender Bias in Pre-trained Filipino FastText Embeddings","authors":["LC Gamboa, MRJ Estuar - 2023 International Conference on IT Innovation and …, 2023"],"snippet":"… This embedding was trained on Common Crawl and Wikipedia data written in Filipino, the Philippine national language based primarily on Tagalog (a regional language in the country) but also containing words from foreign (eg, …","url":["https://ieeexplore.ieee.org/abstract/document/10100022/"]}
{"year":"2023","title":"Evaluating Knowledge Graphs with Hybrid Intelligence","authors":["S Tsaneva"],"snippet":"… WebIsALOD is a large KG containing 400M hypernymy relations, automatically extracted from the CommonCrawl web corpus, describing generic knowledge [6]. The current verification of the resource relies on machine learning models trained …","url":["https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Tsaneva_2023_Evaluating.pdf"]}
{"year":"2023","title":"Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics","authors":["J Holmes, Z Liu, L Zhang, Y Ding, TT Sio, LA McGee… - arXiv preprint arXiv …, 2023"],"snippet":"We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions. Because popular exams like AP Physics, LSAT, and GRE have large test-taker populations and ample test …","url":["https://arxiv.org/pdf/2304.01938"]}
{"year":"2023","title":"Evaluating Paraphrastic Robustness in Textual Entailment Models","authors":["D Verma, YK Lal, S Sinha, B Van Durme, A Poliak"],"snippet":"We presentˆP aRT E, a collection of 1,126 pairs of Recognizing Textual Entailment (RTE) examples to evaluate whether models are robust to paraphrasing. We posit that if RTE models understand language, their predictions should be consistent across …","url":["https://www3.cs.stonybrook.edu/~ylal/files/papers/acl2023.pdf"]}
{"year":"2023","title":"Evaluating Prompt-based Question Answering for Object Prediction in the Open Research Knowledge Graph","authors":["J D'Souza, M Hrou, S Auer - arXiv preprint arXiv:2305.12900, 2023"],"snippet":"There have been many recent investigations into prompt-based training of transformer language models for new text genres in low-resource settings. The prompt-based training approach has been found to be effective in generalizing pre-trained …","url":["https://arxiv.org/pdf/2305.12900"]}
{"year":"2023","title":"Evaluating Rule-Based and Neural Merging Strategies of Entity Clusters for Coreference Resolution","authors":["J Mägdefrau - 2023"],"snippet":"Coreference resolution is an essential pre-processing step for many natural language processing tasks. In the past, there has been a shift from rule-based approaches to machinelearning-based approaches. A recent approach that focuses …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2023-ba-maegdefrau.pdf"]}
{"year":"2023","title":"Evaluating Supervised Machine Learning Models for Zero-Day Phishing Attack Detection: A Comprehensive Study","authors":["Z Lotfi, S Valipourebrahimi, T Tran - 2023"],"snippet":"To have highly secure e-commerce websites, detecting and preventing cyber-attacks is of high importance. Among diverse types of cyber-attacks, identifying zero-day attacks is problematic since they are unknown to the security system. It is because …","url":["https://www.researchsquare.com/article/rs-3204260/latest.pdf"]}
{"year":"2023","title":"Evaluating synthesized speech: the cognitive approach","authors":["G Navickas, GA Melnik-Leroy - DAMSS: 13th conference on data analysis methods …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148640608/148640608.pdf"]}
{"year":"2023","title":"Evaluating Temporal Persistence Using Replicability Measures","authors":["J Keller, T Breuer, P Schaer - arXiv preprint arXiv:2308.10549, 2023"],"snippet":"In real-world Information Retrieval (IR) experiments, the Evaluation Environment (EE) is exposed to constant change. Documents are added, removed, or updated, and the information need and the search behavior of users is evolving. Simultaneously …","url":["https://arxiv.org/pdf/2308.10549"]}
{"year":"2023","title":"Evaluating the Capabilities of Large Language Models for Spatial and Situational Understanding","authors":["S Das"],"snippet":"… With the advent of new generation compute platforms1, curation of large scale datasets like the CommonCrawl2, and the formal verification of the power scaling, development of larger and larger language models boomed. In Table 2.1 we give a …","url":["https://www.researchgate.net/profile/Sowmen-Das/publication/374724794_Evaluating_the_Capabilities_of_Large_Language_Models_for_Spatial_and_Situational_Understanding/links/652ae1b01a05311a23ff0941/Evaluating-the-Capabilities-of-Large-Language-Models-for-Spatial-and-Situational-Understanding.pdf"]}
{"year":"2023","title":"Evaluating the Effectiveness of Pre-trained Language Models in Predicting the Helpfulness of Online Product Reviews","authors":["A Boluki, JPR Sharami, D Shterionov - arXiv preprint arXiv:2302.10199, 2023"],"snippet":"Businesses and customers can gain valuable information from product reviews. The sheer number of reviews often necessitates ranking them based on their potential helpfulness. However, only a few reviews ever receive any helpfulness votes on …","url":["https://arxiv.org/pdf/2302.10199"]}
{"year":"2023","title":"Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning","authors":["S Munikoti, A Acharya, S Wagle, S Horawalavithana - arXiv preprint arXiv:2311.04348, 2023"],"snippet":"… In addition to the ATLAS model pretrained with common crawl (CC) and Wikipedia, we also train ATLAS-Science (220M) model from scratch with the S2ORC scientific text datasets. For a fair comparison with ATLAS, we initialize the ATLAS-Science …","url":["https://arxiv.org/pdf/2311.04348"]}
{"year":"2023","title":"Evaluating the Efficiency of Quantum Simulators Using Practical Application Benchmarks","authors":["RS Kumar - 2023"],"snippet":"Quantum computing holds the potential to revolutionize various industries by solving problems that classical computers cannot solve efficiently. However, building quantum computers is still in its infancy, and simulators are currently the best …","url":["https://search.proquest.com/openview/a187e3790915945e91d6d2d987a6faa8/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Evaluating the Moral Beliefs Encoded in LLMs","authors":["N Scherrer, C Shi, A Feder, DM Blei - arXiv preprint arXiv:2307.14324, 2023"],"snippet":"This paper presents a case study on the design, administration, post-processing, and evaluation of surveys on large language models (LLMs). It comprises two components: (1) A statistical method for eliciting beliefs encoded in LLMs. We …","url":["https://arxiv.org/pdf/2307.14324"]}
{"year":"2023","title":"Evaluation of African American Language Bias in Natural Language Generation","authors":["N Deas, J Grieser, S Kleiner, D Patton, E Turcan… - arXiv preprint arXiv …, 2023"],"snippet":"We evaluate how well LLMs understand African American Language (AAL) in comparison to their performance on White Mainstream English (WME), the encouraged \"standard\" form of English taught in American classrooms. We measure …","url":["https://arxiv.org/pdf/2305.14291"]}
{"year":"2023","title":"Evaluation of ChatGPT Applicability to Learning Quantum Physics","authors":["A Stefńnska, TP Stefański, M Czubenko - 2023 16th International Conference on …, 2023"],"snippet":"ChatGPT is an application that uses a large language model. Its purpose is to generate answers to various questions as well as provide information, help solve problems and participate in conversations on a wide range of topics. This …","url":["https://ieeexplore.ieee.org/abstract/document/10261132/"]}
{"year":"2023","title":"Evaluation of ChatGPT as a Question Answering System for Answering Complex Questions","authors":["Y Tan, D Min, Y Li, W Li, N Hu, Y Chen, G Qi - arXiv preprint arXiv:2303.07992, 2023"],"snippet":"… FLAN-T5 FLAN-T5 (Text-to-Text Transfer Transformer, 11B [8])is an encoderdecoder Transformer language model that is trained on a filtered variant of CommonCrawl (C4) [34]. The release date and model size for this model are also based on [34]. …","url":["https://arxiv.org/pdf/2303.07992"]}
{"year":"2023","title":"Evaluation of Different Machine Learning, Deep Learning and Text Processing Techniques for Hate Speech Detection","authors":["N Shawkat - 2023"],"snippet":"Social media has become a domain that involves a lot of hate speech. Some users feel entitled to engage in abusive conversations by sending abusive messages, tweets, or photos to other users. It is critical to detect hate speech and prevent …","url":["https://bearworks.missouristate.edu/cgi/viewcontent.cgi?article=4958&context=theses"]}
{"year":"2023","title":"Evaluation of Estimating Preschool Children's Verbal Communication Skills in Group Discussions","authors":["H Yamaguchi, K Horio - 2022 Joint 12th International Conference on Soft …, 2022"],"snippet":"In recent years, “First grade problem”, in which first graders who have just entered elementary school are unable to adjust to school life, has been occurring. One of the causes of this problem is a lack of communication skills. Since children have more …","url":["https://ieeexplore.ieee.org/abstract/document/10002023/"]}
{"year":"2023","title":"Evaluation of GPT and BERT-based models on identifying protein-protein interactions in biomedical text","authors":["H Rehana, NB Çam, M Basmaci, Y He, A Özgür, J Hur - arXiv preprint arXiv …, 2023"],"snippet":"Detecting protein-protein interactions (PPIs) is crucial for understanding genetic mechanisms, disease pathogenesis, and drug design. However, with the fast-paced growth of biomedical literature, there is a growing need for automated and accurate …","url":["https://arxiv.org/pdf/2303.17728"]}
{"year":"2023","title":"Evaluation of Language Models on Romanian XQuAD and RoITD datasets","authors":["CD Nicolae, RK Yadav, D Tufiş - INTERNATIONAL JOURNAL OF COMPUTERS …, 2023"],"snippet":"… This multi-language corpus was extracted via language classification, filtered, and cleaned from Common Crawl. Additionally, the latest version of the Wikipedia Dumps for Romanian was obtained, parliamentary debates from 1996-2017 were …","url":["https://fsja.univagora.ro/jour/index.php/ijccc/article/download/5111/1886"]}
{"year":"2023","title":"Evaluation of strategies for the adaptation of large neural models to the task of machine translation in constrained scenarios","authors":["J Iranzo Sánchez - 2023"],"snippet":"[EN] Historically, machine translation (MT) has been one of the most active areas within artificial intelligence and more precisely, within the field of machine learning. Thanks to the significant progress in training large neural networks on massive …","url":["https://riunet.upv.es/bitstream/handle/10251/198517/Iranzo%20-%20Evaluation%20of%20strategies%20for%20the%20adaptation%20of%20large%20neural%20models%20to%20the%20task%20of%20machin....pdf?sequence=1"]}
{"year":"2023","title":"Evidence retrieval for causal questions using query expansion and reranking","authors":["A Gaden, B Reinhold, L Zeit-Altpeter, N Rausch - Working Notes of CLEF, 2023"],"snippet":"We present our runs to the Touché Lab on Argument and Causal Retrieval at CLEF 2023, aiming to retrieve relevant documents for given causal questions. Our approaches rely heavily on query expansions. Both a transformer-based and a …","url":["https://www.dei.unipd.it/~faggioli/temp/CLEF2023-proceedings/paper-262.pdf"]}
{"year":"2023","title":"Examining the effect of whitening on static and contextualized word embeddings","authors":["S Sasaki, B Heinzerling, J Suzuki, K Inui - Information Processing & Management, 2023"],"snippet":"… GloVe840B is trained on the Common Crawl dataset containing 840 billion tokens, while GloVe6B is trained on the Wikipedia and Gigaward dataset containing 6 billion tokens. GNews is trained by using a CBOW algorithm (Mikolov, Chen, et al., 2013) …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323000092"]}
{"year":"2023","title":"Examining the Text-to-Image Community of Practice: Why and How do People Prompt Generative AIs?","authors":["T Sanchez - Proceedings of the 15th Conference on Creativity and …, 2023"],"snippet":"Image generation gained popularity with machine learning (ML) models generating images from text, fuelling new online communities of practices. This work explores the sociology, motivations, and usages of AI art hobbyists. We analyzed an online …","url":["https://hal.science/hal-04127516/document"]}
{"year":"2023","title":"Examining User-Friendly and Open-Sourced Large GPT Models: A Survey on Language, Multimodal, and Scientific GPT Models","authors":["K Gao, S He, Z He, J Lin, QZ Pei, J Shao, W Zhang - arXiv preprint arXiv:2308.14149, 2023"],"snippet":"… GPT-3 [2] devised an automated filtering method to effectively eliminate low-quality documents from the Common Crawl dataset. It used a … Moreover, GPT-3 adopted fuzzy deduplication of documents within each dataset and the removal of WebText …","url":["https://arxiv.org/pdf/2308.14149"]}
{"year":"2023","title":"ExpertQA: Expert-Curated Questions and Attributed Answers","authors":["C Malaviya, S Lee, S Chen, E Sieber, M Yatskar… - arXiv preprint arXiv …, 2023","SL ChaitanyaMalaviya, ES SihaoChen, M Yatskar…"],"snippet":"As language models are adapted by a more sophisticated and diverse set of users, the importance of guaranteeing that they provide factually correct information supported by verifiable sources is critical across fields of study & professions. This is …","url":["https://arxiv.org/pdf/2309.07852","https://cogcomp.seas.upenn.edu/papers/MLCSYR24.pdf"]}
{"year":"2023","title":"Explainable clinical coding with in-domain adapted transformers","authors":["G López-García, JM Jerez, N Ribelles, E Alba… - Journal of Biomedical …, 2023"],"snippet":"Background and Objective Automatic clinical coding is a crucial task in the process of extracting relevant information from unstructured medical documents contained in Electronic Health Records (EHR). However, most of the existing computer-based …","url":["https://www.sciencedirect.com/science/article/pii/S1532046423000448"]}
{"year":"2023","title":"Explainable Crowd Decision Making methodology guided by expert natural language opinions based on Sentiment Analysis with Attention-based Deep Learning and …","authors":["C Zuheros, E Martínez-Cámara, E Herrera-Viedma… - Information Fusion, 2023"],"snippet":"There exist a high demand to provide explainability to artificial intelligence systems, where decision making models are included. This paper focuses on crowd decision making using natural language evaluations from social media with the aim to …","url":["https://www.sciencedirect.com/science/article/pii/S1566253523001379"]}
{"year":"2023","title":"Explainable multi-task convolutional neural network framework for electronic petition tag recommendation","authors":["Z Yang, J Feng - Electronic Commerce Research and Applications, 2023"],"snippet":"Electronic petition (e-petition) is an electronic government (e-government) service that allows citizens to file petitions to governments via the internet. The complexity of the e-petition filing process and the unexplainable e-government tools would reduce …","url":["https://www.sciencedirect.com/science/article/pii/S1567422323000285"]}
{"year":"2023","title":"Explaining Sarcasm of Tweets using Attention Mechanism","authors":["RL Keerthana, AK Singh, P Saini, D Malhotra - Scalable Computing: Practice and …, 2023"],"snippet":"Emotion identification from text can help boost the effectiveness of sentiment analysis models. Sarcasm is one of the more difficult emotions to detect, particularly in textual data. Even though several models for detecting sarcasm have been …","url":["https://www.scpe.org/index.php/scpe/article/view/2166/820"]}
{"year":"2023","title":"Explanatory Argument Extraction of Correct Answers in Resident Medical Exams","authors":["I Goenaga, A Atutxa, K Gojenola, M Oronoz, R Agerri - arXiv preprint arXiv …, 2023"],"snippet":"Developing the required technology to assist medical experts in their everyday activities is currently a hot topic in the Artificial Intelligence research field. Thus, a number of large language models (LLMs) and automated benchmarks have recently …","url":["https://arxiv.org/pdf/2312.00567"]}
{"year":"2023","title":"Exploration of transfer learning capability of multilingual models for text classification","authors":["M Bhargava, K Vijayan, O Anand, G Raina - Proceedings of the 2023 5th International …, 2023"],"snippet":"The use of multilingual models for natural language processing is becoming increasingly popular in industrial and business applications, particularly in multilingual societies. In this study, we investigate the transfer learning capabilities …","url":["https://dl.acm.org/doi/abs/10.1145/3609703.3609711"]}
{"year":"2023","title":"Exploring acceptance of autonomous vehicle policies using KeyBERT and SNA: Targeting engineering students","authors":["J Ha, D Kim - arXiv preprint arXiv:2307.09014, 2023"],"snippet":"This study aims to explore user acceptance of Autonomous Vehicle (AV) policies with improved text-mining methods. Recently, South Korean policymakers have viewed Autonomous Driving Car (ADC) and Autonomous Driving Robot (ADR) as …","url":["https://arxiv.org/pdf/2307.09014"]}
{"year":"2023","title":"Exploring and Repairing Gender Fairness Violations in Word Embedding-based Sentiment Analysis Model through Adversarial Patches","authors":["LS Khoo, JQ Bay, MLK Yap, MK Lim, CY Chong…"],"snippet":"With the advancement of sentiment analysis (SA) models and their incorporation into our daily lives, fairness testing on these models is crucial, since unfair decisions can cause discrimination to a large population. Nevertheless, some challenges in …","url":["https://yangzhou6666.github.io/Files/SANER-Adv-Debiasing.pdf"]}
{"year":"2023","title":"Exploring Applications of NLP to Create Deceptive Sandbox Environments with Honeyfiles","authors":["A Ravi, T Surve - 2023"],"snippet":"Various techniques are in practice to create a sandboxed environment to study malicious actors and/or divert them from gaining access to critical assets. Honeypots and honeynets have long been used to create decoy systems that lure adversaries …","url":["https://osf.io/qpdjw/download"]}
{"year":"2023","title":"Exploring ChatGPT's accuracy and confidence in high-resource languages","authors":["M Pelucchi - 2023"],"snippet":"… web content and of the Common Crawl dataset in different European languages. Although, for example, 1.6% might seem like a very small percentage, all the languages listed are still commonly considered high-resource, which is usually …","url":["https://fse.studenttheses.ub.rug.nl/30857/1/Thesis_MartinoPelucchi.pdf"]}
{"year":"2023","title":"Exploring Divergent Thinking for Cyber Soldier Selection","authors":["PA Albinsson, P Lif"],"snippet":"The Swedish Defence Research Agency is developing a test battery (CyberTest Future Soldiers—CTFS) to select conscript cyber soldier candidates for the Swedish Armed Forces since 2019. Comprising knowledge and ability components, CTFS …","url":["https://www.researchgate.net/profile/Paer-Anders-Albinsson/publication/376190168_Exploring_Divergent_Thinking_for_Cyber_Soldier_Selection/links/656d7e30b1398a779dd960d9/Exploring-Divergent-Thinking-for-Cyber-Soldier-Selection.pdf"]}
{"year":"2023","title":"Exploring Instagram Messages on the Right to Abortion: User Profiling and Natural Language Processing Tasks","authors":["L López Cuerva - 2023"],"snippet":"… [25] presents XLM-R, a Transformer based masked language model on one hundred languages, using more than two terabytes of filtered CommonCrawl data, and it provides substantial gains over previous multilingual models like mBERT [26] …","url":["https://riunet.upv.es/bitstream/handle/10251/197643/Lopez%20-%20Exploring%20Instagram%20Messages%20on%20the%20Right%20to%20Abortion%20User%20Profiling%20and%20Natural%20Language....pdf?sequence=4"]}
{"year":"2023","title":"Exploring natural language processing in mechanical engineering education: Implications for academic integrity","authors":["J Lesage, R Brennan, SE Eaton, B Moya, B McDermott… - International Journal of …, 2023"],"snippet":"In this paper, the authors review extant natural language processing models in the context of undergraduate mechanical engineering education. These models have advanced to a stage where it has become increasingly more difficult to discern …","url":["https://journals.sagepub.com/doi/pdf/10.1177/03064190231166665"]}
{"year":"2023","title":"Exploring Register Variation in Turkish Web Corpus","authors":["S Erten - 14–15 September 2023, University of Mannheim …"],"snippet":"… collected by Common Crawl (commoncrawl. org) and cleaned and pre-processed within Massively Multilingual Modelling of Registers in Web-scale Corpora project run by TurkuNLP team at the University of Turku, Finland. Altogether, the corpus …","url":["https://ids-pub.bsz-bw.de/files/12095/CMC_Corpora_2023_Proceedings_2023.pdf#page=72"]}
{"year":"2023","title":"Exploring Semantic Word Representations for Recognition-Free NLP on Handwritten Document Images","authors":["O Tüselmann, GA Fink - International Conference on Document Analysis and …, 2023"],"snippet":"A semantic analysis of documents offers a wide range of practical application scenarios. Thereby, the combination of handwriting recognizer and textual NLP models constitutes an intuitive solution. However, due to the difficulty of recognizing …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41685-9_6"]}
{"year":"2023","title":"Exploring the Constructicon: Linguistic Analysis of a Computational CxG","authors":["J Dunn - arXiv preprint arXiv:2301.12642, 2023"],"snippet":"Recent work has formulated the task for computational construction grammar as producing a constructicon given a corpus of usage. Previous work has evaluated these unsupervised grammars using both internal metrics (for example, Minimum …","url":["https://arxiv.org/pdf/2301.12642"]}
{"year":"2023","title":"Exploring the Conversations of a Motivational Interviewing Chatbot: A Topic Modeling Approach","authors":["RA Mazloomi"],"snippet":"… GPT-3, alongside the mentioned datasets, was also trained on CommonCrawl, a collection of webpages containing 410 billion words [31]. These models gained state-of-the-art performance on many language task benchmarks, including machine translation …","url":["https://tspace.library.utoronto.ca/bitstream/1807/130535/3/Mazloomi_Rod_Ali_202311_MIS_thesis.pdf"]}
{"year":"2023","title":"Exploring the Cookieverse: A Multi-Perspective Analysis of Web Cookies","authors":["A Rasaii, S Singh, D Gosain, O Gasser - arXiv preprint arXiv:2302.05353, 2023"],"snippet":"Web cookies have been the subject of many research studies over the last few years. However, most existing research does not consider multiple crucial perspectives that can influence the cookie landscape, such as the client's location, the impact of …","url":["https://arxiv.org/pdf/2302.05353"]}
{"year":"2023","title":"Exploring the impact of intermediate languages on machine translation","authors":["AS Oliveira, RS Fernandes - 2023"],"snippet":"The field of translation predates the computer, and as technology has advanced, it has evolved and adapted to new discoveries, constantly striving to become more efficient and precise. Machine translation, an integral part of Natural Language …","url":["https://pantheon.ufrj.br/bitstream/11422/21591/1/ASOliveira.pdf"]}
{"year":"2023","title":"Exploring the limits of early predictive maintenance applying anomaly detection technique","authors":["A Serackis, M Jankauskas - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:148981672/148981672.pdf"]}
{"year":"2023","title":"Exploring the Potential of Large Language models in Traditional Korean Medicine: A Foundation Model Approach to Culturally-Adapted Healthcare","authors":["D Jang, CE Kim - arXiv preprint arXiv:2303.17807, 2023"],"snippet":"… In fact, the pre-training dataset for GPT-3, a model released in 2020 that ChatGPT is based on, is mainly derived from a modified version of Common Crawl (19) in which English-based data accounts for about 50%, while Korean data accounts for …","url":["https://arxiv.org/pdf/2303.17807"]}
{"year":"2023","title":"Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task","authors":["Z Wu, L Zhang, C Cao, X Yu, H Dai, C Ma, Z Liu… - arXiv preprint arXiv …, 2023"],"snippet":"… GPT-3 has a massive 175 billion parameters and was trained on a diverse collection of internet data, including Common Crawl3 and Wikipedia4. GPT-4 is the most powerful LLM to date, a successor of GPT-3. Although the technical details of …","url":["https://arxiv.org/pdf/2304.09138"]}
{"year":"2023","title":"Exploring the Why in AI: Investigating how Visual Question Answering models can be interpreted by post-hoc linguistic and visual explanations","authors":["ECG Strømsvåg - 2023"],"snippet":"With the increase in accuracy and usability of Artificial Intelligence (AI), especially deep neural networks, there has been a big demand for these networks. These methods are implemented in various domains to increase productivity, create new …","url":["https://www.duo.uio.no/bitstream/handle/10852/104443/ecstroms_master_thesis_2023_with_appendix.pdf?sequence=5"]}
{"year":"2023","title":"Exploring zero-shot and joint training cross-lingual strategies for aspect-based sentiment analysis based on contextualized multilingual language models","authors":["D Van Thin, H Quoc Ngo, D Ngoc Hao… - Journal of Information and …, 2023"],"snippet":"Aspect-based sentiment analysis (ABSA) has attracted many researchers' attention in recent years. However, the lack of benchmark datasets for specific languages is a common challenge because of the prohibitive cost of manual annotation. The zero-shot …","url":["https://www.tandfonline.com/doi/pdf/10.1080/24751839.2023.2173843"]}
{"year":"2023","title":"Extended context for InstructGPT with LlamaIndex","authors":["B Zirnstein"],"snippet":"… To train the extensive amount of parameters, a refined version of the Common Crawl dataset1 was used, consisting of almost a trillion … 1https://commoncrawl.org/the-data/ 2The modifications include a “modified initialization, pre-normalization, and …","url":["https://www.researchgate.net/profile/Bruno-Zirnstein/publication/371911146_Extended_context_for_InstructGPT_with_LlamaIndex/links/649bd64e95bbbe0c6efc1345/Extended-context-for-InstructGPT-with-LlamaIndex.pdf"]}
{"year":"2023","title":"Extended Hell (o): A Comprehensive Large-Scale Study on Email Confidentiality and Integrity Mechanisms in the Wild","authors":["B Blechschmidt, B Stock"],"snippet":"The core specifications of electronic mail as used today date back as early as the 1970s. At that time, security did not play a significant role in developing communication protocols. These shortcomings still manifest themselves today in the …","url":["https://swag.cispa.saarland/papers/blechschmidt2023extendedhello.pdf"]}
{"year":"2023","title":"Extracting Geographic Knowledge from Large Language Models: An Experiment","authors":["K Salmas, DA Pantazi, M Koubarakis - … on Knowledge Base Construction from Pre …, 2023"],"snippet":"We perform a thorough analysis of how the inner architecture of large language models behaves whilst extracting geographic knowledge. Our aim is to conclude on whether models actually incorporate geospatial information or simply follow …","url":["https://openreview.net/pdf?id=SqR8UgZXNl"]}
{"year":"2023","title":"Extracting Intersectional Stereotypes from Static and Contextualized Embeddings","authors":["TES Charlesworth, K Ghate, A Caliskan, MR Banaji - 2023"],"snippet":"… text corpora, ranging from static GloVe embeddings trained on 840 billion words from the Common Crawl to contextualized BERT embeddings trained on a combination of Wikipedia and Common Crawl text. For the simplest case of static …","url":["https://osf.io/preprints/psyarxiv/tbuqh/download"]}
{"year":"2023","title":"Extracting Key-Value Pairs in Business Documents","authors":["E Thomas, DS Kafle, IS Mahamoud, A Joseph… - International Conference on …, 2023"],"snippet":"Key-value extraction is a challenging task in document AI, particularly in business documents such as invoices. Accurately extracting key-value pairs from such documents is crucial for downstream tasks like accounting, analytics, and decision-making …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41501-2_3"]}
{"year":"2023","title":"Extracting Mental Health Indicators From English and Spanish Social Media: A Machine Learning Approach","authors":["ME Villa-Pérez, LA Trejo, MB Moin, E Stroulia - IEEE Access, 2023"],"snippet":"… For the English Twitter dataset, we used word vectors trained on Common Crawl from the … The Common Crawl corpus contains petabytes of data collected over 12 years of web … Available: https://commoncrawl.org/the-data/ [56] O. Loyola-González …","url":["https://ieeexplore.ieee.org/iel7/6287639/10005208/10315126.pdf"]}
{"year":"2023","title":"Extracting relations from texts using vector language models and a neural network classifier","authors":["M Shishaev, V Dikovitsky, V Pimeshkov, N Kuprikov… - PeerJ Computer Science, 2023"],"snippet":"The article investigates the possibility of identifying the presence of SKOS (Simple Knowledge Organization System) relations between concepts represented by terms on the base of their vector representation in general natural language models …","url":["https://peerj.com/articles/cs-1636/"]}
{"year":"2023","title":"Extracting representative subset from extensive text data for training pre-trained language models","authors":["J Suzuki, H Zen, H Kazawa - Information Processing & Management, 2023"],"snippet":"This paper investigates the existence of a representative subset obtained from a large original dataset that can achieve the same performance level obtained using the entire dataset in the context of training neural language models. We employ the …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322003508"]}
{"year":"2023","title":"Extracting Training Data from GPT-2","authors":["J Borkar"],"snippet":"… We collect tokens from the Common Crawl dataset and use them (5-10 tokens) as prefixes to prompt GPT-2 to generate samples. … Common Crawl dataset has all the data that has been crawled from the public internet. So if we prompt GPT-2 using …","url":["https://jaydeepborkar.github.io/7150_project_report.pdf"]}
{"year":"2023","title":"Extraction of microservices from monolithic software based on the database model","authors":["D Mažeika, EK Kazlauskas - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:147344326/147344326.pdf"]}
{"year":"2023","title":"Extraction of Parallel Sentences","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"… billion parallel sentences in 90 languages from CommonCrawl snapshots, among which less than … This system, trained from parallel sentences collected from CommonCrawl as explained … sentence embeddings to extract parallel sentences …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_4"]}
{"year":"2023","title":"Extractive Summarization of Telugu Text Using Modified Text Rank and Maximum Marginal Relevance","authors":["A Babu Gl, S Badugu - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"With the rapid growth of digital content, the need for the automatic text summarizer is arising to provide short text from the long text document. Many research works have been presented for extractive text summarization (ETS). This paper mainly focuses …","url":["https://dl.acm.org/doi/pdf/10.1145/3600224"]}
{"year":"2023","title":"Förenkla nyhetssammanfattning med hjälp av AI: En analys av GPT-3 modellers förmåga och begränsningar","authors":["J Pålsmark, TA Viklund - 2023"],"snippet":"Everyday we are flooded with news from all around the world and this information can be overwhelming. In our study we analyze the possibilities to implement GPT-3 models in the work of news summarization in swedish and automize this process. In …","url":["https://www.diva-portal.org/smash/get/diva2:1760660/FULLTEXT01.pdf"]}
{"year":"2023","title":"Face Recognition in the age of CLIP & Billion image datasets","authors":["A Bhat, S Jain - arXiv preprint arXiv:2301.07315, 2023"],"snippet":"… LAION-5B was collected by parsing files in the Common Crawl dataset to find image tags with alt-text values. The corresponding images were downloaded and filtered using CLIP to keep only those images whose content resembled their alt-text …","url":["https://arxiv.org/pdf/2301.07315"]}
{"year":"2023","title":"Factors Affecting the Reliability of Information: The Case of ChatGPT","authors":["J Morato, JM Diaz-Nafria, S Sanchez-Cuadrado - International Conference on …, 2023"],"snippet":"The abundance of current information makes it necessary to select the highest quality documents. For this purpose, it is necessary to deepen the knowledge of information quality systems. The different dimensions of quality are analyzed, and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-48930-3_12"]}
{"year":"2023","title":"Fairness and Bias in Algorithmic Hiring","authors":["A Fabris, N Baranowska, MJ Dennis, P Hacker… - arXiv preprint arXiv …, 2023"],"snippet":"… Bias in Bios, [60] is composed of textual biographies written in English and extracted from the Common Crawl dataset. It was initially proposed to study fairness in occupation classification. Gender is automatically extracted based on the use of …","url":["https://arxiv.org/pdf/2309.13933"]}
{"year":"2023","title":"Fairness and Fair Use in Generative AI","authors":["M Sag - 2023"],"snippet":"Although we are still a long way from the science fiction version of artificial general intelligence that thinks, feels, and refuses to “open the pod bay doors”, 1 recent advances in machine learning and artificial intelligence (“AI”) have captured the …","url":["https://digitalcommons.wcl.american.edu/cgi/viewcontent.cgi?article=1120&context=research"]}
{"year":"2023","title":"Fairness in Language Models Beyond English: Gaps and Challenges","authors":["K Ramesh, S Sitaram, M Choudhury - arXiv preprint arXiv:2302.12578, 2023"],"snippet":"With language models becoming increasingly ubiquitous, it has become essential to address their inequitable treatment of diverse demographic groups and factors. Most research on evaluating and mitigating fairness harms has been concentrated on …","url":["https://arxiv.org/pdf/2302.12578"]}
{"year":"2023","title":"Fake News Detection via Deep Learning Approaches","authors":["M Li - 2023 4th International Symposium on Computer …, 2023"],"snippet":"… RealNews: RealNews is a corpus of news articles whose data is taken from Common Crawl. The body and metadata in each news article is extracted by the Newspaper Python library. The training data uses news data from December 2016 to March 2019. …","url":["https://ieeexplore.ieee.org/abstract/document/10271110/"]}
{"year":"2023","title":"Fake news detection: Taxonomy and comparative study","authors":["F Farhangian, RMO Cruz, GDC Cavalcanti - Information Fusion, 2023"],"snippet":"The proliferation of social networks has presented a significant challenge in combating the pervasive issue of fake news within modern societies. Due to the large amount of information and news produced daily in text, audio, and video, the …","url":["https://www.sciencedirect.com/science/article/pii/S1566253523004566"]}
{"year":"2023","title":"Faking It: Artificial Intelligence in a Human World","authors":["T Walsh - 2023"]}
{"year":"2023","title":"Fast and Energy-Efficient Inference for Attention-Based Natural Language Processing Models","authors":["A Hadi Zadeh - 2023","AH Zadeh - 2023"],"snippet":"Creating machines that can ``understand’’ our language and ``interact’’ with us as we interact with each other has been a dream that motivated many and captured the imaginations of even more. Attention-Based Transformer models have demonstrated …","url":["https://search.proquest.com/openview/8ef0b6a759aff7cf22bf26f40affd1bd/1?pq-origsite=gscholar&cbl=18750&diss=y","https://tspace.library.utoronto.ca/bitstream/1807/128003/3/Hadi_Zadeh_Ali_202306_PhD_thesis.pdf"]}
{"year":"2023","title":"Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature","authors":["G Bao, Y Zhao, Z Teng, L Yang, Y Zhang - arXiv preprint arXiv:2310.05130, 2023"],"snippet":"Large language models (LLMs) have shown the ability to produce fluent and cogent content, presenting both productivity opportunities and societal risks. To build trustworthy AI systems, it is imperative to distinguish between machine-generated …","url":["https://arxiv.org/pdf/2310.05130"]}
{"year":"2023","title":"Feature Learning in Infinite-Depth Neural Networks","authors":["G Yang, D Yu, C Zhu, S Hayou - NeurIPS 2023 Workshop on Mathematics of Modern …, 2023"],"snippet":"… block is deeper (such as modern transformers), then we find fundamental limitations in all possible infinite-depth limits of such parametrizations, which we illustrate both theoretically and empirically on simple networks as well as Megatron …","url":["https://openreview.net/forum?id=xxYfmRTwyX"]}
{"year":"2023","title":"Feature-Level Ensemble Learning for Robust Synthetic Text Detection with DeBERTaV3 and XLM-RoBERTa","authors":["SS Joy, TD Aishi - Proceedings of ALTA, 2023"],"snippet":"As large language models, or LLMs, continue to advance in recent years, they require the development of a potent system to detect whether a text was created by a human or an LLM in order to prevent the unethical use of LLMs. To address this …","url":["https://alta2023.alta.asn.au/files/st_04.pdf"]}
{"year":"2023","title":"Federated Learning with Client-Exclusive Classes","authors":["J Zhang, X Zhang, X Zhang, D Hong, RK Gupta… - arXiv preprint arXiv …, 2023"],"snippet":"Existing federated classification algorithms typically assume the local annotations at every client cover the same set of classes. In this paper, we aim to lift such an assumption and focus on a more general yet practical non-IID setting where every …","url":["https://arxiv.org/pdf/2301.00489"]}
{"year":"2023","title":"Few-Shot Learning for Identification of COVID-19 Symptoms Using Generative Pre-trained Transformer Language Models","authors":["K Jiang, M Zhu, GR Bernard - Machine Learning and Principles and Practice of …, 2023"],"snippet":"Since the onset of the COVID-19 pandemic, social media users have shared their personal experiences related to the viral infection. Their posts contain rich information of symptoms that may provide useful hints to advancing the knowledge …","url":["https://link.springer.com/chapter/10.1007/978-3-031-23633-4_21"]}
{"year":"2023","title":"Few-shot Learning with Multilingual Generative Language Models","authors":["XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen… - Proceedings of the 2022 …, 2022"],"snippet":"… As such we also note the potential difference in genres between CommonCrawl and the genres used in GPT-3 comprising in addition to CommonCrawl, corpora such as BookCorpus and Wikipedia. Moreover, GPT-3 is trained on 118 languages …","url":["https://aclanthology.org/2022.emnlp-main.616.pdf"]}
{"year":"2023","title":"Filtering and Extended Vocabulary based Translation for Low-resource Language pair of Sanskrit-Hindi","authors":["P Jha, R Kumar, V Sahula - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"… We used the reported Model 3 (Hindi to Sanskrit) and fed it with a small fraction of monolingual Hindi data (about 10k small sentences from CommonCrawl6 as used by [29]) to generate Sanskrit translations. We used a small fraction of the data to …","url":["https://dl.acm.org/doi/pdf/10.1145/3580495"]}
{"year":"2023","title":"Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training","authors":["F Radenovic, A Dubey, A Kadian, T Mihaylov… - arXiv preprint arXiv …, 2023"],"snippet":"Vision-language models trained with contrastive learning on large-scale noisy data are becoming increasingly popular for zero-shot recognition problems. In this paper we improve the following three aspects of the contrastive pre-training pipeline …","url":["https://arxiv.org/pdf/2301.02280"]}
{"year":"2023","title":"FIMO: A Challenge Formal Dataset for Automated Theorem Proving","authors":["C Liu, J Shen, H Xin, Z Liu, Y Yuan, H Wang, W Ju… - arXiv preprint arXiv …, 2023"],"snippet":"We present FIMO, an innovative dataset comprising formal mathematical problem statements sourced from the International Mathematical Olympiad (IMO) Shortlisted Problems. Designed to facilitate advanced automated theorem proving at the IMO …","url":["https://arxiv.org/pdf/2309.04295"]}
{"year":"2023","title":"Financial Machine Learning with Alternative Data","authors":["J Jiang - 2023"],"snippet":"In the first chapter, we reconsider the idea of trend-based predictability using methods that flexibly learn price patterns that are most predictive of future returns, rather than testing hypothesized or pre-specified patterns (eg, momentum and …","url":["https://search.proquest.com/openview/98f583e53d755e34bc8666ecf40c317f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Findings of the 2023 Conference on Machine Translation (WMT23): LLMs Are Here But Not Quite There Yet","authors":["K Tom, E Avramidis, R Bawden, O Bojar, A Dvorkovich… - WMT23-Eighth Conference …, 2023"],"snippet":"This paper presents the results of the General Machine Translation Task organised as part of the 2023 Conference on Machine Translation (WMT). In the general MT task, participants were asked to build machine translation systems for any of 8 …","url":["https://hal.science/hal-04300702/document"]}
{"year":"2023","title":"Findings of the CoCo4MT 2023 Shared Task on Corpus Construction for Machine Translation","authors":["A Ganesh, M Carpuat, W Chen, K Kann, C Lignos… - CoCo4MT 2023, 2023"],"snippet":"This paper provides an overview of the first shared task on choosing beneficial instances for machine translation, conducted as part of the CoCo4MT 2023 Workshop at MTSummit. This shared task was motivated by the need to make the …","url":["https://files.sciconf.cn/upload/file/20230903/20230903151747_19845.pdf#page=34"]}
{"year":"2023","title":"Findings of the Second WMT Shared Task on Sign Language Translation","authors":["M Müller, M Alikhani, E Avramidis, R Bowden, A Braffort…"],"snippet":"This paper presents the results of the Second WMT Shared Task on Sign Language Translation (WMT-SLT23) 1. This shared task is concerned with automatic translation between signed and spoken 2 languages. The task is unusual in the …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.4.pdf"]}
{"year":"2023","title":"Findings of the WMT 2023 shared task on parallel data curation","authors":["S Sloto, B Thompson, H Khayrallah, T Domhan… - Proceedings of the Eighth …, 2023"],"snippet":"… We release processed Common Crawl data, along with various intermediate states from a strong baseline system, which we believe will … All of our inputs were derived from the 2023-06 snapshot of Common Crawl. We extracted the plain text …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.5.pdf"]}
{"year":"2023","title":"Fine Tuning Transformer Models for Domain Specific Feature Extraction","authors":["C Campàs Gené - 2023"],"snippet":"The nature of Natural Language Processing has drastically changed in the past years. The implementation of Large Language Models pre-trained on thousands of unlabelled data has opened the door to a new layer of comprehension of text …","url":["https://upcommons.upc.edu/bitstream/handle/2117/384726/173985.pdf?sequence=2"]}
{"year":"2023","title":"Fine-Grained Language Relatedness for Zero-Shot Silesian-English Translation","authors":["E Signoroni - RASLAN 2023 Recent Advances in Slavonic Natural …, 2023"],"snippet":"… -cleaned version of the Common Crawl web dump containing about 750GB of English text. T5 uses a unified” text-to-text” format for all text-based NLP problems. Xue et al.(2021)[29] present mT5, a multilingual variant of T5 trained on a Common …","url":["http://nlp.fi.muni.cz/raslan/raslan23.pdf#page=153"]}
{"year":"2023","title":"Fine-tuning MBART-50 with French and Farsi data to improve the translation of Farsi dislocations into English and French","authors":["B Namdarzadeh, S Mohseni, L Zhu, G Wisniewski… - Proceedings of Machine …, 2023"],"snippet":"In this paper, we discuss the improvements brought by the fine-tuning of mBART50 for the translation of a specific Farsi dataset of dislocations. Given our BLEU scores, our evaluation is mostly qualitative: we assess the improvements of our fine-tuning …","url":["https://aclanthology.org/2023.mtsummit-users.14.pdf"]}
{"year":"2023","title":"FinGPT: Large Generative Models for a Small Language","authors":["R Luukkonen, V Komulainen, J Luoma, A Eskelinen… - arXiv preprint arXiv …, 2023"],"snippet":"… Common Crawl and a targeted Internet crawl seeded by the .fi domain registry content and all URLs of Finnish material in Common Crawl. … CC-Fi To maximize coverage of Finnish text in Common Crawl resources, we applied a custom …","url":["https://arxiv.org/pdf/2311.05640"]}
{"year":"2023","title":"Finnish Internet Parsebank","authors":["J Luotolahti, J Kanerva, J Luoma, V Skantsi, S Pyysalo… - 2023"],"snippet":"… The Common Crawl dataset includes both plain text and raw HTML files, at the time without … plain text from the Amazon cloud service that hosts Common Crawl As shown in Table 2, this … of all Finnish text pages we gathered from Common …","url":["https://www.researchsquare.com/article/rs-3138153/latest.pdf"]}
{"year":"2023","title":"Focused Crawling for Automated IsiXhosa Corpus Building","authors":["C Marquard, H Suleman - Annual Conference of South African Institute of …, 2023"],"snippet":"IsiXhosa is a low-resource language, which means that it does not have many large, high-quality corpora. This makes it difficult to perform many kinds of research with the language. This paper examines the use of focused Web crawling for automatic …","url":["https://link.springer.com/chapter/10.1007/978-3-031-39652-6_2"]}
{"year":"2023","title":"Form to meaning mapping and the impact of explicit morpheme combination in novel word processing","authors":["R Bonandrini, S Amenta, S Sulpizio, M Tettamanti… - Cognitive Psychology, 2023"],"snippet":"In the present study, we leveraged computational methods to explore the extent to which, relative to direct access to semantics from orthographic cues, the additional appreciation of morphological cues is advantageous while inducing the meaning of …","url":["https://www.sciencedirect.com/science/article/pii/S001002852300052X"]}
{"year":"2023","title":"Foundation Models and Fair Use","authors":["P Henderson, X Li, D Jurafsky, T Hashimoto… - arXiv preprint arXiv …, 2023"],"snippet":"… 2021), rely on CommonCrawl data which is crawled only if users explicitly allow it through their robots.txt file. CommonCrawl is able to host a snapshot of the internet largely because of fair use arguments. As the organization’s director argues, there is …","url":["https://arxiv.org/pdf/2303.15715"]}
{"year":"2023","title":"Foundation models and the privatization of public knowledge","authors":["F Ferrari, J van Dijck, A van den Bosch - Nature Machine Intelligence, 2023"],"snippet":"… This translates to approximately 300 billion words extracted from sources such as Wikipedia, CommonCrawl and GitHub. Overall, the training procedure involved the learning of 175 billion parameters. ChatGPT relies on GPT-4 as well as on a specific …","url":["https://www.nature.com/articles/s42256-023-00695-5"]}
{"year":"2023","title":"Foundation Models in Robotics: Applications, Challenges, and the Future","authors":["R Firoozi, J Tucker, S Tian, A Majumdar, J Sun, W Liu… - arXiv preprint arXiv …, 2023"],"snippet":"… GPT-3 is trained on the Common Crawl dataset. Common Crawl contains petabytes of publicly available data over 12 years of web crawling and includes raw web page data, metadata, and text extracts. LLMs can also be multilingual. For …","url":["https://arxiv.org/pdf/2312.07843"]}
{"year":"2023","title":"Foundational Models Defining a New Era in Vision: A Survey and Outlook","authors":["M Awais, M Naseer, S Khan, RM Anwer, H Cholakkal… - arXiv preprint arXiv …, 2023"],"snippet":"… common crawl. Schuhmann et al. [227] further scaled it up and released a multilingual, multi-modal dataset called LAION-5B which contains 5.8 billion data points curated from Common Crawl after filtering through existing CLIP model. Utilizing largescale …","url":["https://arxiv.org/pdf/2307.13721"]}
{"year":"2023","title":"FP8-LM: Training FP8 Large Language Models","authors":["H Peng, K Wu, Y Wei, G Zhao, Y Yang, Z Liu, Y Xiong… - arXiv preprint arXiv …, 2023"],"snippet":"… 2022) across CommonCrawl snapshots to enhance data quality. Tab. 10 in Appendix A.3 provides details of our pre-training data, including … 2023) to distinguish documents similar to Wikipedia pages from randomly sampled …","url":["https://arxiv.org/pdf/2310.18313"]}
{"year":"2023","title":"From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models","authors":["M Suzuki, M Hirano, H Sakaji - arXiv preprint arXiv:2309.03412, 2023"],"snippet":"Instruction tuning is essential for large language models (LLMs) to become interactive. While many instruction tuning datasets exist in English, there is a noticeable lack in other languages. Also, their effectiveness has not been well …","url":["https://arxiv.org/pdf/2309.03412"]}
{"year":"2023","title":"From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding","authors":["L Sun, F Luisier, K Batmanghelich, D Florencio… - arXiv preprint arXiv …, 2023"],"snippet":"… Most generic language models are pre-trained on web-crawled text corpora including Wikipedia and Common Crawl. But in real world deployments, models are often used in a different domain, an issue referred to as domain shift. In order to …","url":["https://arxiv.org/pdf/2305.14571"]}
{"year":"2023","title":"From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy","authors":["M Gupta, CK Akiri, K Aryal, E Parker, L Praharaj - arXiv preprint arXiv:2307.00691, 2023"],"snippet":"… Initially, GPT-1 was trained with the Common Crawl dataset, made up of web pages, and the BookCorpus dataset, which contained over … GPT-2: GPT-2 was trained on Common Crawl just like GPT-1 but combined that with WebText, which …","url":["https://arxiv.org/pdf/2307.00691"]}
{"year":"2023","title":"From chocolate bunny to chocolate crocodile: Do Language Models Understand Noun Compounds?","authors":["J Coil, V Shwartz - arXiv preprint arXiv:2305.10568, 2023"],"snippet":"Noun compound interpretation is the task of expressing a noun compound (eg chocolate bunny) in a free-text paraphrase that makes the relationship between the constituent nouns explicit (eg bunny-shaped chocolate). We propose modifications …","url":["https://arxiv.org/pdf/2305.10568"]}
{"year":"2023","title":"From GPT to AutoGPT: a Brief Attention in NLP Processing using DL","authors":["M Fezari, AAD Ali-Al-Dahoud"],"snippet":"in this paper, we intend to present the evolution of the so called “Generative Pre-Training (GPT) models”. Starting from GPT-1 to the new one GPt-4 and AutoGPT, Generative Pre-Training (GPT) models are trained on unlabeled dataset (which are available in …","url":["https://www.researchgate.net/profile/Mohamed-Fezari-2/publication/370107237_From_GPT_to_AutoGPT_a_Brief_Attention_in_NLP_Processing_using_DL/links/643fd87a2eca706c8b6d151b/From-GPT-to-AutoGPT-a-Brief-Attention-in-NLP-Processing-using-DL.pdf"]}
{"year":"2023","title":"From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning","authors":["D Zaikis, I Vlahavas - IEEE Access, 2023"],"snippet":"Language representation learning is a vital field in Natural Language Processing (NLP) that aims to capture the intricate semantics and contextual information of text. With the advent of deep learning and neural network architectures, representation …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10288436.pdf"]}
{"year":"2023","title":"From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models","authors":["S Feng, CY Park, Y Liu, Y Tsvetkov - arXiv preprint arXiv:2305.08283, 2023"],"snippet":"Large language models (LMs) are pretrained on diverse data sources: news, discussion forums, books, online encyclopedias. A significant portion of this data includes facts and opinions which, on one hand, celebrate democracy and diversity …","url":["https://arxiv.org/pdf/2305.08283"]}
{"year":"2023","title":"From task to evaluation: an automatic text summarization review","authors":["L Lu, Y Liu, W Xu, H Li, G Sun - Artificial Intelligence Review, 2023"],"snippet":"Automatic summarization is attracting increasing attention as one of the most promising research areas. This technology has been tried in various real-world applications in recent years and achieved a good response. However, the …","url":["https://link.springer.com/article/10.1007/s10462-023-10582-5"]}
{"year":"2023","title":"From Text to Source: Results in Detecting Large Language Model-Generated Content","authors":["W Antoun, B Sagot, D Seddah - arXiv preprint arXiv:2309.13322, 2023"],"snippet":"The widespread use of Large Language Models (LLMs), celebrated for their ability to generate human-like text, has raised concerns about misinformation and ethical implications. Addressing these concerns necessitates the development of robust …","url":["https://arxiv.org/pdf/2309.13322"]}
{"year":"2023","title":"From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference","authors":["S Samsi, D Zhao, J McDonald, B Li, A Michaleas… - arXiv preprint arXiv …, 2023"],"snippet":"… Like other LLMs, LLaMA was pre-trained on a large collection of data including but not limited to CommonCrawl, Github, Wikipedia, etc. As of spring 2023, alongside other recently timed releases of state-of-the-art LLMs such as Google’s …","url":["https://arxiv.org/pdf/2310.03003"]}
{"year":"2023","title":"From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning","authors":["Q Liu, F Zhou, Z Jiang, L Dou, M Lin - arXiv preprint arXiv:2304.07995, 2023"],"snippet":"Fine-tuning language models on tasks with instructions has demonstrated potential in facilitating zero-shot generalization to unseen tasks. In this paper, we introduce a straightforward yet effective method for enhancing instruction tuning by employing …","url":["https://arxiv.org/pdf/2304.07995"]}
{"year":"2023","title":"FSTP Project Report AID2030–ArtificialIn-telligenceDataKit2030","authors":["S Koeva, V Stefanova - 2023"],"snippet":"… CommonCrawl29 creates and maintains an open web crawl data collection. Petabytes of data have been collected by Common Crawl since 2008, including … RealNews33 is a dataset of news articles from Common Crawl. The text and the …","url":["https://european-language-equality.eu/wp-content/uploads/2023/06/ELE2_Project_Report_AID_2030.pdf"]}
{"year":"2023","title":"Fundamentals of Generative Large Language Models and Perspectives in Cyber-Defense","authors":["A Kucharavy, Z Schillaci, L Maréchal, M Würsch… - arXiv preprint arXiv …, 2023"],"snippet":"… to train GPT-2, along with a filtered and deduplicated version of the Common Crawl, a dataset of all the text that can be found by a crawl on … from Wikipedia is likely to be seen on average 3.4 times during the training compared to 0.44 times for …","url":["https://arxiv.org/pdf/2303.12132"]}
{"year":"2023","title":"GAIA Search: Hugging Face and Pyserini Interoperability for NLP Training Data Exploration","authors":["A Piktus, O Ogundepo, C Akiki, A Oladipo, X Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"… Rather than investing in scraping the Web on their own, dataset creators typically turn to Common Crawl1 as the main source of text to include in their corpora. A repository of Web snapshots dating back to 2011, Common Crawl contains various …","url":["https://arxiv.org/pdf/2306.01481"]}
{"year":"2023","title":"GEM: Gestalt Enhanced Markup Language Model for Web Understanding via Render Tree","authors":["Z Shao, F Gao, Z Qi, H Xing, J Bu, Z Yu, Q Zheng, X Liu - Proceedings of the 2023 …, 2023"],"snippet":"… Our corpora are built from the Common Crawl12 dataset. We derive approximately 2 million training samples from 100k renderable web pages by pre-processing. Details of the data pre-processing are available in Section 3.1. … 12https://commoncrawl.org/ …","url":["https://aclanthology.org/2023.emnlp-main.375.pdf"]}
{"year":"2023","title":"Gender stereotypes embedded in natural language are stronger in more economically developed and individualistic countries","authors":["C Napp - PNAS Nexus, 2023"],"snippet":"… Relying on two different sources (Wikipedia and Common Crawl), we found that these gender stereotypes are all significantly more pronounced in the text corpora of more economically developed and more individualistic countries. Our analysis …","url":["https://academic.oup.com/pnasnexus/article/2/11/pgad355/7429364"]}
{"year":"2023","title":"Gender stereotypes in neural sentence representations","authors":["A Al Ali - 2023"],"snippet":"Neural networks have seen a spike in popularity in natural language processing in re- cent years. They consistently outperform the traditional methods and require less human labor to perfect as they are trained unsupervised on large text corpora …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/184287/130369737.pdf?sequence=1"]}
{"year":"2023","title":"Gender Stereotypes in User-Generated Content","authors":["A Kerkhof, V Reich - 2023"],"snippet":"Gender stereotypes pose an important hurdle on the way to gender equality. It is difficult to quantify the problem, though, as stereotypical beliefs are often subconscious or not openly expressed. User-generated content (UGC) opens up …","url":["https://www.cesifo.org/DocDL/cesifo1_wp10578.pdf"]}
{"year":"2023","title":"Generating a Large Web Traffic Dataset","authors":["BC Simmonds - 2023"],"snippet":"… Resource Locators) from the Common Crawl dataset as a foundational … the Common Crawl dataset, by requesting each website of the collection to measure the required server response time. Nonetheless, this solution has its drawbacks …","url":["https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/632737/Simmonds_Benjamin.pdf?sequence=1"]}
{"year":"2023","title":"Generating abstract art using artificial neural networks","authors":["H Norrman"],"snippet":"Articial intelligence (AI) tools are slowly becoming integral to our everyday lives. Today we already rely on AI for much of our navigation and security. In the near future, much like the internet today, AI and machine learning tools are likely to assist …","url":["https://lup.lub.lu.se/student-papers/record/9142136/file/9142137.pdf"]}
{"year":"2023","title":"Generating plumitifs descriptions using neural networks","authors":["N Garneau - 2023"],"snippet":"Comme dans de nombreuses autres démocraties, il existe au Canada un droit d'accès à l'information judiciaire. Il s' agit d'un élément fondamental de tout processus judiciaire. Ce droit a deux objectifs principaux: offrir une fenêtre sur le système de …","url":["https://corpus.ulaval.ca/bitstreams/34518b78-5505-40c4-8d13-8bec62840aa6/download"]}
{"year":"2023","title":"Generating Query Focused Summaries without Fine-tuning the Transformer-based Pre-trained Models","authors":["D Abdullah, S Nayak, G Suri, Y Chali - arXiv preprint arXiv:2303.06230, 2023"],"snippet":"Fine-tuning the Natural Language Processing (NLP) models for each new data set requires higher computational time associated with increased carbon footprint and cost. However, fine-tuning helps the pre-trained models adapt to the latest data sets; …","url":["https://arxiv.org/pdf/2303.06230"]}
{"year":"2023","title":"Generating Synthetic Data from Large Language Models","authors":["S Choenni, T Busker, MS Bargh - 2023 15th International Conference on Innovations …, 2023"],"snippet":"Data collection for studying social phenomena is not only costly but is also, at best, a time-consuming and tedious task. Therefore, tools that may ease the task of data collection will speed up these studies and improve their efficiency. In this contribution …","url":["https://ieeexplore.ieee.org/abstract/document/10366424/"]}
{"year":"2023","title":"Generation of Synthetic Responses to Survey Questions Using GPT-3: A Case of Hard-to-Reach Members of Russian Elites (based on the Survey of Russian Elites)","authors":["K Kalinin"],"snippet":"The goal of this study is to use a large language model, such as GPT-3, to generate responses from hard-to-reach elite members to multiple-choice questions. The most relevant or data-consistent responses can then be used to infer potential responses …","url":["https://kirillkalinin.com/files/paper_gpt3.pdf"]}
{"year":"2023","title":"Generations: Creative Computation, Community, and the Rhetorical Canon","authors":["C Schnitzler - 2023"],"snippet":"“Generations: Creative Computation, Community, and the Rhetorical Canon” investigates how computational poets and artists use the intrinsic rhetoricity of generative computational processes for social critique and community-building …","url":["https://cdr.lib.unc.edu/downloads/794087356"]}
{"year":"2023","title":"Generative AI and Lexicography: The Current State of the Art Using ChatGPT","authors":["GM de Schryver - International Journal of Lexicography, 2023"],"snippet":"In this article, all ten papers and talks that have been devoted to the use of ChatGPT in lexicography so far are critically analysed, their results tabulated and cross-compared, from which the leading trends are determined. Extrapolating from the trendlines, a …","url":["https://academic.oup.com/ijl/advance-article/doi/10.1093/ijl/ecad021/7288213"]}
{"year":"2023","title":"Generative AI and the Digital Commons","authors":["S Huang, D Siddarth - arXiv preprint arXiv:2303.11074, 2023"],"snippet":"… They also rely on nonprofits like Common Crawl (which build and maintain open repositories of web crawl data), Creative Commons (for open licenses for the data used), open source libraries, and other digital infrastructure. They also take …","url":["https://arxiv.org/pdf/2303.11074"]}
{"year":"2023","title":"Generative AI Considered Harmful","authors":["JE Fischer - 2023"],"snippet":"The recent months have seen an explosion of interest, hype, and concern about generative AI, driven by the release of ChatGPT. In this article I seek to explicate some potential and actual harms of the engineering and use of generative AI such …","url":["https://www.cs.nott.ac.uk/~pszjf1/papers/Fischer_CUI23.pdf"]}
{"year":"2023","title":"Generative AI for Medical Imaging: extending the MONAI Framework","authors":["WHL Pinaya, MS Graham, E Kerfoot, PD Tudosiu… - arXiv preprint arXiv …, 2023"],"snippet":"… -hungry, they have thrived in fields with large publicly available datasets, such as computer vision, with datasets like ImageNet [8] and LAION [43], as well as natural language processing (with access to large textual corpora, like the Wikipedia Text …","url":["https://arxiv.org/pdf/2307.15208"]}
{"year":"2023","title":"Generative AI for Semantic Communication: Architecture, Challenges, and Outlook","authors":["L Xia, Y Sun, C Liang, L Zhang, MA Imran, D Niyato - arXiv preprint arXiv:2308.15483, 2023"],"snippet":"… Through pretraining on large datasets (like Wikipedia and Common Crawl) and fine-tuning on user data (to be more personalized and customized), GPT-Neo is capable to be directly installed into TDs to precisely extract keywords of source …","url":["https://arxiv.org/pdf/2308.15483"]}
{"year":"2023","title":"Generative AI in Academic Writing, Ethical Recommendations","authors":["C Forrester, K Boothe"],"snippet":"As the use of Artificial Intelligence (AI) tools such as Generative Pre-trained Transformers (GPTs) becomes more prevalent in academic writing, there are growing concerns about the ethical implications of their use. This article addresses …","url":["https://www.researchgate.net/profile/Clive-Forrester/publication/369858017_Generative_AI_in_Academic_Writing_Ethical_Recommendations/links/64c27798cda2775c03c9d0a2/Generative-AI-in-Academic-Writing-Ethical-Recommendations.pdf"]}
{"year":"2023","title":"Generative approach for gender-rewriting task with ArabicT5","authors":["S Alrowili, K Vijay-Shanker - Proceedings of the The Seventh Arabic Natural …, 2022"],"snippet":"… 2021) is a multilingual variant of T5, which was pre-trained on the new Common Crawl-based dataset that consists of 6.3T tokens covering 101 languages. The mT5 model also uses a large vocabulary file that consists of 250K tokens. …","url":["https://aclanthology.org/2022.wanlp-1.55.pdf"]}
{"year":"2023","title":"Generative Artificial Intelligence through ChatGPT and Other Large Language Models in Ophthalmology: Clinical Applications and Challenges","authors":["TF Tan, AJ Thirunavukarasu, JP Campbell, PA Keane… - Ophthalmology Science"],"snippet":"The rapid progress of large language models (LLMs) driving generative artificial intelligence applications heralds the potential of opportunities in healthcare. We conducted a review up to April 2023 on Google Scholar, Embase, MEDLINE, and …","url":["https://www.ophthalmologyscience.org/article/S2666-9145(23)00126-4/fulltext"]}
{"year":"2023","title":"Generative Artificial Intelligence: A Double-Edged Sword","authors":["K Kuck - 2023 World Engineering Education Forum-Global …, 2023"],"snippet":"… Stable Diffusion was trained with three massive image datasets collected by the nonprofit LAION, which built their datasets from CommonCrawl, another nonprofit that scrapes through the internet monthly and releases datasets of what they …","url":["https://ieeexplore.ieee.org/abstract/document/10343638/"]}
{"year":"2023","title":"Generative Artificial Intelligence: Fundamentals","authors":["JM Corchado, S López, R Garcia, P Chamoso - ADCAIJ: Advances in Distributed …, 2023"],"snippet":"Generative language models have witnessed substantial traction, notably with the introduction of refined models aimed at more coherent user-AI interactions—principally conversational models. The epitome of this public attention has arguably been the …","url":["https://revistas.usal.es/cinco/index.php/2255-2863/article/download/31704/29998"]}
{"year":"2023","title":"Generative Benchmark Creation for Table Union Search","authors":["K Pal, A Khatiwada, R Shraga, RJ Miller - arXiv preprint arXiv:2308.03883, 2023"],"snippet":"Data management has traditionally relied on synthetic data generators to generate structured benchmarks, like the TPC suite, where we can control important parameters like data size and its distribution precisely. These benchmarks were …","url":["https://arxiv.org/pdf/2308.03883"]}
{"year":"2023","title":"Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations By admin 6 Comments","authors":["JA Goldstein, G Sastry, M Musser, R DiResta… - 2023"],"snippet":"In recent years, artificial intelligence (AI) systems have significantly improved and their capabilities have expanded. In particular, AI systems called “generative models” have made great progress in automated content creation, such as images generated …","url":["https://your-restaurant-ai.com/generative-language-models-and-automated-influence-operations-emerging-threats-and-potential-mitigations/"]}
{"year":"2023","title":"Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations","authors":["JA Goldstein, G Sastry, M Musser, R DiResta… - arXiv preprint arXiv …, 2023"],"snippet":"Generative language models have improved drastically, and can now produce realistic text outputs that are difficult to distinguish from human-written content. For malicious actors, these language models bring the promise of automating the …","url":["https://arxiv.org/pdf/2301.04246"]}
{"year":"2023","title":"Generative Language Models Exhibit Social Identity Biases","authors":["T Hu, Y Kyrychenko, S Rathje, N Collier… - arXiv preprint arXiv …, 2023"],"snippet":"The surge in popularity of large language models has given rise to concerns about biases that these models could learn from humans. In this study, we investigate whether ingroup solidarity and outgroup hostility, fundamental social biases known …","url":["https://arxiv.org/pdf/2310.15819"]}
{"year":"2023","title":"Generative Language Models for Automated Programming Feedback","authors":["L Hedberg Segeholm, E Gustafsson - 2023"],"snippet":"In recent years, Generative Language Models have exploded into the mainstream with household names like BERT and ChatGPT, proving that text generation could have the potential to solve a variety of tasks. As the number of students enrolled into …","url":["https://www.diva-portal.org/smash/get/diva2:1784396/FULLTEXT01.pdf"]}
{"year":"2023","title":"Generative Pre-trained Transformer: A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions","authors":["G Yenduri, G Srivastava, PKR Maddikunta, RH Jhaveri… - arXiv preprint arXiv …, 2023"],"snippet":"… 500 billion words called ”Common Crawl” that was gathered from a sizable content archive and the internet [30]. Its other noteworthy and unexpected capability is its ability to carry out basic mathematical operations, write bits of code, and carry …","url":["https://arxiv.org/pdf/2305.10435"]}
{"year":"2023","title":"Generative Pretraining in Multimodality","authors":["Q Sun, Q Yu, Y Cui, F Zhang, X Zhang, Y Wang, H Gao… - arXiv preprint arXiv …, 2023"],"snippet":"We present Emu, a Transformer-based multimodal foundation model, which can seamlessly generate images and texts in multimodal context. This omnivore model can take in any single-modality or multimodal data input indiscriminately (eg …","url":["https://arxiv.org/pdf/2307.05222"]}
{"year":"2023","title":"Geoparsing at Web-scale-Challenges and Opportunities","authors":["SM Farzana, T Hecking - 2023"],"snippet":"The increasing amount of web data being generated and stored along with geographic information is of great importance to enrich future search applications in science, news, economics, etc.. In addition to location information provided by users …","url":["https://ceur-ws.org/Vol-3385/paper6.pdf"]}
{"year":"2023","title":"Geopolitical Forecasting Analysis of the Russia-Ukraine War Using the Expert's Survey, Predictioneer's Game and GPT-3","authors":["K Kalinin - Predictioneer's Game and GPT-3 (April 8, 2023), 2023"],"snippet":"The Russia-Ukraine war that began on February 24th has resulted in significant geopolitical upheaval, sending shockwaves that reverberated around the globe. This extended and highly destructive war continues to rage on without any apparent …","url":["https://kirillkalinin.com/files/paper_forecasting.pdf"]}
{"year":"2023","title":"German Compounds in Transformer Models","authors":["K Neumannová - 2023"],"snippet":"German is known for its highly productive word formation processes, particularly in the area of compounding and derivation. In this thesis, we focus on German nominal compounds and their representation in machine translation (MT) outputs. Despite …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/181571/120445862.pdf?sequence=1"]}
{"year":"2023","title":"German Question Tags: A Computational Analysis","authors":["Y Clausen - Proceedings http://ceur-ws. org ISSN, 2023"],"snippet":"The German language exhibits a range of question tags that can typically, but not always, be substituted for one another. Moreover, the same words can have other meanings while occurring in the sentence-昀椀 nal position. The tags’ felicity …","url":["https://ceur-ws.org/Vol-3558/paper5269.pdf"]}
{"year":"2023","title":"GERNERMED++: Semantic annotation in German medical NLP through transfer-learning, translation and word alignment","authors":["J Frei, L Frei-Stuber, F Kramer - Journal of Biomedical Informatics, 2023"],"snippet":"We present a statistical model, GERNERMED++, for German medical natural language processing trained for named entity recognition (NER) as an open, publicly available model. We demonstrate the effectiveness of combining multiple …","url":["https://www.sciencedirect.com/science/article/pii/S1532046423002344"]}
{"year":"2023","title":"Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs","authors":["F Kang, HA Just, Y Sun, H Jahagirdar, Y Zhang, R Du…"],"snippet":"This work focuses on leveraging and selecting from vast, unlabeled, open data to pre-fine-tune a pre-trained language model. The goal is to minimize the need for costly domain-specific data for subsequent fine-tuning while achieving desired performance levels …","url":["https://neurips2023-enlsp.github.io/papers/paper_35.pdf"]}
{"year":"2023","title":"GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network","authors":["R Jia, H Guo, X Jin, C Yan, L Du, X Ma, T Stankovic… - Proceedings of the 29th …, 2023"],"snippet":"… However, the dataset mainly contains small and medium size tables [16] from the Common Crawl, and we observe that the tables have a relatively simple structure. Additionally, the dataset only contains 386 samples, leading to high variance in its …","url":["https://dl.acm.org/doi/abs/10.1145/3580305.3599366"]}
{"year":"2023","title":"GIO: Gradient Information Optimization for Training Dataset Selection","authors":["D Everaert, C Potts - arXiv preprint arXiv:2306.11670, 2023"],"snippet":"… [4] develop a heuristic method to filter CommonCrawl based on a trained classifier’s probability that datapoints are high quality. Similarly, … an analysis of undesirable content in the Common Crawl corpus. In Proceedings of the 59th Annual Meeting of …","url":["https://arxiv.org/pdf/2306.11670"]}
{"year":"2023","title":"GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks","authors":["S Gupta, C Rosenbaum, ER Elenberg - arXiv preprint arXiv:2311.09606, 2023"],"snippet":"Large language models (LLMs) have the ability to perform in-context learning (ICL) of new tasks by conditioning on prompts comprising a few task examples. This work studies the problem of selecting the best examples given a candidate pool to …","url":["https://arxiv.org/pdf/2311.09606"]}
{"year":"2023","title":"GiusBERTo: Italy's AI-Based Judicial Transformation: A Teaching Case","authors":["P Datta, BJ Zahn, L Attias, G Salierno, R Bertè… - Communications of the …, 2023"],"snippet":"In an age when open access to law enforcement files and judicial documents can erode individual privacy and confidentiality, miscreants can abuse this open access to personal information for blackmail, misinformation, and even social engineering …","url":["https://aisel.aisnet.org/cais/vol53/iss1/33/"]}
{"year":"2023","title":"Gloss Alignment using Word Embeddings","authors":["H Walsh, OM Sincan, B Saunders, R Bowden - 2023 IEEE International Conference …, 2023"],"snippet":"… The models are trained on the Common Crawl and Wikipedia datasets and have an output dimension of 300. For the following experiments we use the English implementation when testing our approach on the BOBSL dataset and the German …","url":["https://ieeexplore.ieee.org/abstract/document/10193013/"]}
{"year":"2023","title":"GlotScript: A Resource and Tool for Low Resource Writing System Identification","authors":["AH Kargaran, F Yvon, H Schütze - arXiv preprint arXiv:2309.13320, 2023"],"snippet":"We present GlotScript, an open resource and tool for low resource writing system identification. GlotScript-R is a resource that provides the attested writing systems for more than 7,000 languages. It is compiled by aggregating information from existing …","url":["https://arxiv.org/pdf/2309.13320"]}
{"year":"2023","title":"GMNLP at SemEval-2023 Task 12: Sentiment Analysis with Phylogeny-Based Adapters","authors":["MMI Alam, R Xie, F Faisal, A Anastasopoulos - arXiv preprint arXiv:2304.12979, 2023"],"snippet":"This report describes GMU's sentiment analysis system for the SemEval-2023 shared task AfriSenti-SemEval. We participated in all three sub-tasks: Monolingual, Multilingual, and Zero-Shot. Our approach uses models initialized with AfroXLMR-large …","url":["https://arxiv.org/pdf/2304.12979"]}
{"year":"2023","title":"GNN-based retrieval and recommadation system: A semantic enhenced graph model","authors":["L Wang, X Li, H Zhang, Y Dai, S Zhang - 2022 IEEE 5th Advanced Information …, 2022"],"snippet":"As a general method that captures knowledge from relation, graph modeling has been widely used in many fields including recommendation in Internet applications. A typical graph based system must be provided with a nodes and edges. To get …","url":["https://ieeexplore.ieee.org/abstract/document/10019945/"]}
{"year":"2023","title":"Google Bard Artificial Intelligence versus the 2022 Self-Assessment Study Program for Urology","authors":["LM Huynh, BT Bonebrake, K Schultis, A Quach… - Urology Practice, 2023"],"snippet":"… While Bard’s training dataset has been largely undisclosed by its Google developers, a 2022 paper discussing the underlying LaMDA model [5] found its training set composition to be 50% from online public forums, 12.5% from Wikipedia …","url":["https://www.auajournals.org/doi/abs/10.1097/UPJ.0000000000000453"]}
{"year":"2023","title":"GPT (Generative Pre-trained Transformer)–A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions","authors":["G Yenduri, M Ramalingam, G Chemmalar Selvi…"],"snippet":"… It is taught using a corpus of 500 billion words called ”Common Crawl” that was gathered from a sizable content archive and the internet [26]. Its other noteworthy and unexpected capability is its ability to carry out basic mathematical operations …","url":["https://www.researchgate.net/profile/Gokul-Yenduri/publication/370869544_Generative_Pre-trained_Transformer_A_Comprehensive_Review_on_Enabling_Technologies_Potential_Applications_Emerging_Challenges_and_Future_Directions/links/646b4adf2d0a4c58bef111cd/Generative-Pre-trained-Transformer-A-Comprehensive-Review-on-Enabling-Technologies-Potential-Applications-Emerging-Challenges-and-Future-Directions.pdf"]}
{"year":"2023","title":"GPT is an effective tool for multilingual psychological text analysis","authors":["S Rathje, DM Mirea, I Sucholutsky, R Marjieh… - 2023"],"snippet":"… Our analyses so far have focused on widely-spoken languages that are relatively highly represented in CommonCrawl – a large repository … eight of these languages, some of which had less than 20 million speakers (Table 1) and relatively little …","url":["https://psyarxiv.com/sekf5/download?format=pdf"]}
{"year":"2023","title":"GPT takes the Bar Exam","authors":["MJB IIa, DM Katza"],"snippet":"… As reported in [19], OpenAI’s models are trained on a combination of curated CommonCrawl data and high-quality reference data that, if we consider The Pile V1 as reference [24], may have included some material from public legal sources …","url":["https://smallake.kr/wp-content/uploads/2023/01/SSRN-id4314839.pdf"]}
{"year":"2023","title":"GPT-3 for Education; Benefits and Concerns","authors":["MIZ Abidin, A Alkhalidi, F Mustaffa - … Conference on Creative Multimedia 2023 (ICCM …, 2023"],"snippet":"… It was trained on publicly available data, including the Common Crawl dataset, which contains a vast amount of text from the web. GPT-3 excels in language translation, question answering, and human-like text generation. Compared to …","url":["https://www.atlantis-press.com/article/125994266.pdf"]}
{"year":"2023","title":"GPT-3 Models are Few-Shot Financial Reasoners","authors":["RS de Padua, I Qureshi, MU Karakaplan - arXiv preprint arXiv:2307.13617, 2023"],"snippet":"… GPT-3 is a 175B parameter autoregressive language model trained on 45TB from CommonCrawl, Wikipedia and others, showing state-of-the-art performance on many NLP-related tasks. Often these tasks can be performed by providing a relevant …","url":["https://arxiv.org/pdf/2307.13617"]}
{"year":"2023","title":"GPT-3 vs Object Oriented Programming Assignments: An Experience Report","authors":["BP Cipriano, P Alves - Proceedings of the 2023 Conference on Innovation …, 2023"],"snippet":"… We were also curious about GPT’s capacity to reply to prompts written in a language other than English, since it gathers information from the Common Crawl dataset which is primarily comprised of English content (46% as of 2022) [9]. All of …","url":["https://dl.acm.org/doi/pdf/10.1145/3587102.3588814"]}
{"year":"2023","title":"GPT-4 can pass the Korean National Licensing Examination for Korean Medicine Doctors","authors":["D Jang, TR Yun, CY Lee, YK Kwon, CE Kim - PLOS Digital Health, 2023"],"snippet":"… For example, the pre-training dataset for GPT-3, a model released in 2020 that GPT-3.5 is based on and the technical details have been officially reported, is mainly derived from a modified version of Common Crawl [19] in which English-based data …","url":["https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000416"]}
{"year":"2023","title":"GPT-4 For Developers","authors":["O Campesato - 2024"],"snippet":"This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=98_qEAAAQBAJ&oi=fnd&pg=PP13&dq=commoncrawl&ots=kALFZg_NdN&sig=ZBrEFhqJsDOAfqb1zDuAUVwbpPY"]}
{"year":"2023","title":"Gradient Ascent Post-training Enhances Language Model Generalization","authors":["D Yoon, J Jang, S Kim, M Seo - arXiv preprint arXiv:2306.07052, 2023"],"snippet":"… We consider OPT LMs to be familiar (in-domain) to Common Crawl, as it was included in their pretraining corpora. As OPT LMs were not explicitly trained on the Github corpora we consider OPT to be unfamiliar (out-ofdistribution) with Github …","url":["https://arxiv.org/pdf/2306.07052"]}
{"year":"2023","title":"Grammatical Error Correction with byte-level language models","authors":["M Jentoft - 2023"],"snippet":"… It is pre-trained on over a hundred languages on the multilingual dataset named mC4: multilingual Colossal Cleaned Common Crawl. The training of the model mirrors that of t5 closely, but differs both in that is was trained on a multilingual …","url":["https://www.duo.uio.no/bitstream/handle/10852/103885/5/jentoft_masteroppgave_2023.pdf"]}
{"year":"2023","title":"GreekBART: The First Pretrained Greek Sequence-to-Sequence Model","authors":["I Evdaimon, H Abdine, C Xypolopoulos, S Outsios… - arXiv preprint arXiv …, 2023"],"snippet":"The era of transfer learning has revolutionized the fields of Computer Vision and Natural Language Processing, bringing powerful pretrained models with exceptional performance across a variety of tasks. Specifically, Natural Language Processing …","url":["https://arxiv.org/pdf/2304.00869"]}
{"year":"2023","title":"GreekT5: A Series of Greek Sequence-to-Sequence Models for News Summarization","authors":["N Giarelis, C Mastrokostas, N Karacapilidis - arXiv preprint arXiv:2311.07767, 2023"],"snippet":"Text summarization (TS) is a natural language processing (NLP) subtask pertaining to the automatic formulation of a concise and coherent summary that covers the major concepts and topics from one or multiple documents. Recent advancements in …","url":["https://arxiv.org/pdf/2311.07767"]}
{"year":"2023","title":"GRI: Graph-based Relative Isomorphism of Word Embedding Spaces","authors":["MA Ali, Y Hu, J Qin, D Wang - arXiv preprint arXiv:2310.12360, 2023"],"snippet":"… In order to validate these claims for GRI, we re-run the experiments using target embeddings trained on 33.8 million lines of web-crawl data from the English Common Crawl data. The embeddings for the source languages (“bn\", “uk\" and “ta\") …","url":["https://arxiv.org/pdf/2310.12360"]}
{"year":"2023","title":"GRILLBot-v2: Generative Models for Multi-Modal Task-Oriented Assistance","authors":["S Fischer, N Tecklenburg, P Zubel, E Kupcova…"],"snippet":"… Figure 2 shows how our pipeline converts raw textual task sources (Common Crawl, Wikipedia, WikiHow) into an augmented TaskGraph corpus using LLMs, external knowledge sources, and multi-modal content. Specifically for Common …","url":["https://assets.amazon.science/f3/75/cbd31079434eaf0c171a1ae0c8a8/grill-tb2-final-2023.pdf"]}
{"year":"2023","title":"GTCOM and DLUT's Neural Machine Translation Systems for WMT23","authors":["H Zong, C Bei, C Yuan, W Chen, H Liu, D Huang"],"snippet":"This paper presents the submission by Global Tone Communication Co., Ltd. and Dalian Univeristy of Technology for the WMT23 shared general Machine Translation (MT) task at the Conference on Empirical Methods in Natural Language Processing (EMNLP) …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.20.pdf"]}
{"year":"2023","title":"Hallucinating Machines: Exploring the ethical implications of generative language models","authors":["M Hill - 2023"],"snippet":"… OpenAI utilised a filtered version of the Common Crawl dataset as the foundation of the training dataset for GPT-3 (Brown et al., 2020). The Common Crawl dataset comprises petabytes of web data collected since 2008 (So You’re Ready to Get …","url":["https://openaccess.wgtn.ac.nz/articles/thesis/Hallucinating_Machines_Exploring_the_ethical_implications_of_generative_language_models/24180456/1/files/42424206.pdf"]}
{"year":"2023","title":"Hallucinations in Large Multilingual Translation Models","authors":["NM Guerreiro, D Alves, J Waldendorf, B Haddow… - arXiv preprint arXiv …, 2023"],"snippet":"Large-scale multilingual machine translation systems have demonstrated remarkable ability to translate directly between numerous languages, making them increasingly appealing for real-world applications. However, when deployed in the …","url":["https://arxiv.org/pdf/2303.16104"]}
{"year":"2023","title":"HARMONY@ DravidianLangTech: Transformer-based Ensemble Learning for Abusive Comment Detection","authors":["A Murugappan, LP RS, M Deivamani - Proceedings of the Third Workshop on …, 2023"],"snippet":"Millions of posts and comments are created every minute as a result of the widespread use of social media and easy access to the internet. It is essential to create an inclusive environment and forbid the use of abusive language against any …","url":["https://aclanthology.org/2023.dravidianlangtech-1.21.pdf"]}
{"year":"2023","title":"Hate Speech Detection in Hindi","authors":["PP Bansod - 2023"],"snippet":"Social media is a great place to share one’s thoughts and to express oneself. Very often the same social media platforms become a means for spewing hatred. The large amount of data being shared on these platforms make it difficult to moderate …","url":["https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=2265&context=etd_projects"]}
{"year":"2023","title":"Hate speech: semi-automatic recognition in Slovak texts","authors":["L HORNÍKOVÁ"],"snippet":"… This could be caused by the data on which was the FastText model trained (texts from Wikipedia – which primarily represent scientific language style – and Common Crawl). Hate speech is likely underrepresented in the training data; perhaps the data …","url":["https://is.muni.cz/th/ncomq/Hate_speech_semi-automatic_recognition_in_Slovak_texts.pdf"]}
{"year":"2023","title":"HatEmoTweet: Low Level Emotion Classifications and Spatio-Temporal Trends of Hate and Offensive COVID-19 Tweets","authors":["A Adesokan, S Madria, L Nguyen - 2023"],"snippet":"Social media platforms (like Twitter) positively and negatively impact users in diverse societies; one of Twitter’s negative effects is the usage of hate and offensive language. Hate speech fosters prejudice; it also harms the vulnerable. There are …","url":["https://www.researchsquare.com/article/rs-2696349/latest.pdf"]}
{"year":"2023","title":"HC3: A Suite of Test Collections for CLIR Evaluation over Informal Text","authors":["D Lawrie, J Mayfield, DW Oard, E Yang, S Nair… - Proceedings of the 46th …, 2023"],"snippet":"While there are many test collections for Cross-Language Information Retrieval (CLIR), none of the large public test collections focus on short informal text documents. This paper introduces a new pair of CLIR test collections with millions of Chinese or …","url":["https://user.eng.umd.edu/~oard/pdf/sigir23-hc3.pdf"]}
{"year":"2023","title":"HeRo: RoBERTa and Longformer Hebrew Language Models","authors":["V Shalumov, H Haskey - arXiv preprint arXiv:2304.11077, 2023"],"snippet":"In this paper, we fill in an existing gap in resources available to the Hebrew NLP community by providing it with the largest so far pre-train dataset HeDC4, a state-of-the-art pre-trained language model HeRo for standard length inputs and an efficient …","url":["https://arxiv.org/pdf/2304.11077"]}
{"year":"2023","title":"HHLD: Hateful posts Identification in Hindi Language leveraging multi task learning","authors":["P Kapil, G Kumari, A Ekbal, S Pal, A Chatterjee… - IEEE Access, 2023"],"snippet":"… 2.5 TB of common crawl data in 100 languages are used to train it. It outperforms M-BERT across cross-lingual classification, especially for low-resource languages. To apply sub-word tokenization on the raw input, sentence piece [50] with unigram …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10243565.pdf"]}
{"year":"2023","title":"Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus","authors":["A Piergentili, B Savoldi, D Fucci, M Negri, L Bentivogli - arXiv preprint arXiv …, 2023"],"snippet":"Gender inequality is embedded in our communication practices and perpetuated in translation technologies. This becomes particularly apparent when translating into grammatical gender languages, where machine translation (MT) often defaults to …","url":["https://arxiv.org/pdf/2310.05294"]}
{"year":"2023","title":"Hierarchical Representations From Large Mathematical Corpora","authors":["L Berlioz - 2023"],"snippet":"… Examples of common corpora used in NLP include Project Gutenberg1, which is an online library of more that 60,000 free ebooks [83]; the Common Crawl data set2 is a large collection of data from internet websites. And, of particular importance to …","url":["http://d-scholarship.pitt.edu/43650/1/Berlioz%20-%20PhD%20-%20ETD%20-%20v1.3.pdf"]}
{"year":"2023","title":"High-Efficiency Device-Cloud Collaborative Transformer Model","authors":["P Jiang, K Xin, C Li, Y Zhou - Proceedings of the IEEE/CVF Conference on Computer …, 2023"],"snippet":"Natural Language Processing (NLP) experts have had significant success with unsupervised language pre-training techniques. However, compared to typical NLP models, modern self-attention models require far more computational and memory …","url":["https://openaccess.thecvf.com/content/CVPR2023W/MobileAI/papers/Jiang_High-Efficiency_Device-Cloud_Collaborative_Transformer_Model_CVPRW_2023_paper.pdf"]}
{"year":"2023","title":"HODI at EVALITA 2023: Overview of the first Shared Task on Homotransphobia Detection in Italian","authors":["D Nozza, AT Cignarella, G Damo, T Caselli, V Patti - Proceedings of EVALITA, 2023"],"snippet":"HODI is a new shared task for the automatic detection of homotransphobia in Italian presented at EVALITA 2023. The challenge is organized into two subtasks: Subtask A focuses on the binary textual classification of homotransphobic tweets, while …","url":["https://ceur-ws.org/Vol-3473/paper26.pdf"]}
{"year":"2023","title":"Home Evolving Standards of Care Demystifying AI: Current Insights on Artificial Intelligence in Thoracic Oncology","authors":["RH Mak, F Haugg"],"snippet":"… ChatGPT was trained on a diverse mix of datasets, including a dataset known as Common Crawl,4 which alone contains nearly a trillion words before filtering. It is worth noting that this model learns in an unsupervised manner—it does not rely on …","url":["https://www.ilcn.org/demystifying-ai-current-insights-on-artificial-intelligence-in-thoracic-oncology/"]}
{"year":"2023","title":"HOMOCHAR: A novel adversarial attack framework for exposing the vulnerability of text based neural sentiment classifiers","authors":["A Bajaj, DK Vishwakarma - Engineering Applications of Artificial Intelligence, 2023"],"snippet":"… In addition, RoBERTa had also been trained on datasets which include CC-News (Common Crawl-News), Open WebText, and others. These datasets have a combined size of about 160 GB. RoBERTa used a batch size of 8000 with 300,000 …","url":["https://www.sciencedirect.com/science/article/pii/S0952197623009995"]}
{"year":"2023","title":"Homophobia and transphobia detection for low-resourced languages in social media comments","authors":["PK Kumaresan, R Ponnusamy, R Priyadharshini… - Natural Language …, 2023"],"snippet":"… It’sa multilingual language model with 2.5 TB of filtered Common Crawl data that was trained. XLM-RoBERTa was fine-tuned for evaluation and inference on a range of downstream tasks using Wikipedia data in over 100 languages. XLM-RoBERTa …","url":["https://www.sciencedirect.com/science/article/pii/S2949719123000389"]}
{"year":"2023","title":"Honey, I Shrunk the Language: Language Model Behavior at Reduced Scale","authors":["V Deshpande, D Pechi, S Thatte, V Lialin, A Rumshisky - arXiv preprint arXiv …, 2023"],"snippet":"In recent years, language models have drastically grown in size, and the abilities of these models have been shown to improve with scale. The majority of recent scaling laws studies focused on high-compute high-parameter count settings, leaving the …","url":["https://arxiv.org/pdf/2305.17266"]}
{"year":"2023","title":"HOW CHATGPT CAN BE USED FOR A CONTRACT DRAFTING CLASS","authors":["BL Fernandez, K Hardy - 2023"],"snippet":"… • The Common Crawl dataset (https://commoncrawl.org), …","url":["https://scholarship.law.wm.edu/cgi/viewcontent.cgi?article=1014&context=incorporating_chatgpt"]}
{"year":"2023","title":"How Deep Contextualized Representation and Attention Mechanism Justifies Explainable Cross-lingual Sentiment Analysis","authors":["R Ghasemi, S Momtazi - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"… It has been pre-trained on the CommonCrawl Corpus, containing 100 languages with 2.5TB of data. Considering the advantages of LSTM models in capturing words’ sequential behavior, we build an LSTM-based classiier on the top of XLM-RoBERTa …","url":["https://dl.acm.org/doi/pdf/10.1145/3626094"]}
{"year":"2023","title":"How Does Calibration Data Affect the Post-training Pruning and Quantization of Large Language Models?","authors":["M Williams, N Aletras - arXiv preprint arXiv:2311.09755, 2023"],"snippet":"… This consists of English web text from Common Crawl, filtered with heuristics that form a “… This mainly consists of web text (Common Crawl and C4), in addition to high-quality sources … was created from stringent filtering and deduplication of …","url":["https://arxiv.org/pdf/2311.09755"]}
{"year":"2023","title":"How far can we get in creating a digital replica of a philosopher?","authors":["A Strasser, E Schwitzgebel, M Crosby - 2023"],"snippet":"Can we build machines with which we can have interesting conversations? Observing the new optimism of AI regarding deep learning and new language models, we set ourselves an ambitious goal: We want to find out how far we can get …","url":["https://philpapers.org/archive/STRHFC.pdf"]}
{"year":"2023","title":"How Language-Dependent is Emotion Detection? Evidence from Multilingual BERT","authors":["L De Bruyne, P Singh, O De Clercq, E Lefever, V Hoste - 2nd Workshop on Multi …, 2022"],"snippet":"As emotion analysis in text has gained a lot of attention in the field of natural language processing, differences in emotion expression across languages could have consequences for how emotion detection models work. We evaluate the …","url":["https://biblio.ugent.be/publication/01GPDJHVE9ESH8GJ8ABEA50S2J/file/01GPDJR6BDK37SDZ15VTQS7Z81"]}
{"year":"2023","title":"How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations?","authors":["F Jourdan, TT Kaninku, N Asher, JM Loubes, L Risser - arXiv preprint arXiv …, 2023"],"snippet":"… Note that to build this dataset, its authors used Common Crawl and identified online biographies written in English. Then, they filtered the biographies starting with a name-like pattern followed by the string “is a(n) (xxx) title,” where title is an …","url":["https://arxiv.org/pdf/2302.14063"]}
{"year":"2023","title":"How Prevalent is Gender Bias in ChatGPT?--Exploring German and English ChatGPT Responses","authors":["S Urchs, V Thurner, M Aßenmacher, C Heumann… - arXiv preprint arXiv …, 2023"],"snippet":"… It is unclear from the documentation on which data the system was trained exactly, but since it includes training data from CommonCrawl4 it is likely to reflect many of the biases and stereotypes common to internet content. Furthermore, the model is …","url":["https://arxiv.org/pdf/2310.03031"]}
{"year":"2023","title":"How to deploy security mechanisms online (consistently)","authors":["S Roth - 2023"],"snippet":"To mitigate a myriad of Web attacks, modern browsers support client-side security policies shipped through HTTP response headers. To enforce these policies, the operator can set response headers that the server then communicates to the client …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/35991/1/thesis.pdf"]}
{"year":"2023","title":"How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases","authors":["A Mueller, T Linzen - arXiv preprint arXiv:2305.19905, 2023"],"snippet":"… All of these models are trained on approximately 34B words from the Colossal Cleaned Common Crawl (C4) web text corpus. … , which we included in the previous experiment, we also pre-train models on the Colossal Cleaned Common …","url":["https://arxiv.org/pdf/2305.19905"]}
{"year":"2023","title":"How User Language Affects Conflict Fatality Estimates in ChatGPT","authors":["D Kazenwadel, CV Steinert - arXiv preprint arXiv:2308.00072, 2023"],"snippet":"OpenAI's ChatGPT language model has gained popularity as a powerful tool for complex problem-solving and information retrieval. However, concerns arise about the reproduction of biases present in the language-specific training data. In this study …","url":["https://arxiv.org/pdf/2308.00072"]}
{"year":"2023","title":"How well do language models understand grammar?: a case study on Japanese","authors":["GC Breul - 2022"],"snippet":"Modern attention-based language models such as BERT and GPT have been shown to outperform previous state-of-the-art models on many NLP tasks. This performance implies a level of understanding of grammatical structures. This work …","url":["http://elib.uni-stuttgart.de/bitstream/11682/12803/1/Masterarbeit%20Gerhard%20Breul.pdf"]}
{"year":"2023","title":"HPLT: High Performance Language Technologies","authors":["M Aulamo, N Bogoychev, S Ji, G Nail… - Proceedings of the 24th …, 2023"],"snippet":"We describe the High Performance Language Technologies project (HPLT), a 3-year EU-funded project started in September 2022. HPLT will build a space combining petabytes of natural language data with large-scale model training. It will derive …","url":["https://aclanthology.org/2023.eamt-1.61.pdf"]}
{"year":"2023","title":"HTTP header based phishing attack detection using machine learning","authors":["S Shukla, M Misra, G Varshney - Transactions on Emerging Telecommunications …"],"snippet":"In the past, many techniques like blacklisting/whitelisting, third‐party, search engine, visual similarity, heuristic, URL features, and website content were used for anti‐phishing. Search engine‐based, third‐party assisted tools and blacklist/whitelist fail to identify …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/ett.4872"]}
{"year":"2023","title":"HUAWEI NOAH'S ARK LAB AT TREC NEUCLIR 2022","authors":["E Kamalloo, D Alfonso-Hermelo, M Rezagholizadeh"],"snippet":"… Both corpora are collected from the Common Crawl news collection. To identify documents in Chinese, Persian, and Russian, the language of documents were determined via automated language identification. HC4 comprises documents within …","url":["https://trec.nist.gov/pubs/trec31/papers/huaweimtl.N.pdf"]}
{"year":"2023","title":"HULAT at SemEval-2023 Task 10: Data augmentation for pre-trained transformers applied to the detection of sexism in social media","authors":["I Segura-Bedmar - arXiv preprint arXiv:2302.12840, 2023"],"snippet":"This paper describes our participation in SemEval-2023 Task 10, whose goal is the detection of sexism in social media. We explore some of the most popular transformer models such as BERT, DistilBERT, RoBERTa, and XLNet. We also study …","url":["https://arxiv.org/pdf/2302.12840"]}
{"year":"2023","title":"HULAT at SemEval-2023 Task 9: Data augmentation for pre-trained transformers applied to Multilingual Tweet Intimacy Analysis","authors":["I Segura-Bedmar - arXiv preprint arXiv:2302.12794, 2023"],"snippet":"This paper describes our participation in SemEval-2023 Task 9, Intimacy Analysis of Multilingual Tweets. We fine-tune some of the most popular transformer models with the training dataset and synthetic data generated by different data augmentation …","url":["https://arxiv.org/pdf/2302.12794"]}
{"year":"2023","title":"Human intelligence-based metaverse for co-learning of students and smart machines","authors":["CS Lee, MH Wang, M Reformat, SH Huang - Journal of Ambient Intelligence and …, 2023"],"snippet":"This paper proposes a Human Intelligence (HI)-based Computational Intelligence (CI) and Artificial Intelligence (AI) Fuzzy Markup Language (CI&AI-FML) Metaverse as an educational environment for co-learning of students and machines. The HI-based …","url":["https://link.springer.com/article/10.1007/s12652-023-04580-2"]}
{"year":"2023","title":"Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment","authors":["A Peña, I Serna, A Morales, J Fierrez, A Ortega… - arXiv preprint arXiv …, 2023"],"snippet":"… In the study of demographic bias in NLP technologies,4 we can cite the Common Crawl Bios dataset [31], which contains nearly 400K short biographies collected from Common Crawl. The goal of the dataset is to predict the occupation from these …","url":["https://arxiv.org/pdf/2302.10908"]}
{"year":"2023","title":"Humanoid Robot as a Debate Partner","authors":["HS Yun, H Hübert, A Sardogan, N Pinkwart, VV Hafner… - International Conference on …, 2023"],"snippet":"In this paper, we describe our design and development process of a humanoid robot, Pepper, as a debate partner by integrating open-source, offline Generative Pre-trained Transformer models, namely GPT-J 6B and BLOOM. We used our tool flow, which …","url":["https://link.springer.com/chapter/10.1007/978-3-031-36004-6_74"]}
{"year":"2023","title":"HunSum-1: an Abstractive Summarization Dataset for Hungarian","authors":["B Barta, D Lakatos, A Nagy, MK Nyist, J Ács - arXiv preprint arXiv:2302.00455, 2023"],"snippet":"… In Section 3 we discuss in detail how we extracted the data from CommonCrawl and performed a number of preprocessing steps to arrive at the current version of HunSum-1. We also train three baseline models on the dataset and evaluate the results both …","url":["https://arxiv.org/pdf/2302.00455"]}
{"year":"2023","title":"HW-TSC's Neural Machine Translation System for CCMT 2023","authors":["Z Wu, Z Yu, Z Li, D Wei, Y Xie, X Chen, H Shang, J Guo… - China Conference on …, 2023"],"snippet":"This paper presents Huawei Translation Service Center (HW-TSC)’s submission to the machine translation tasks of the 19th China Conference on Machine Translation (CCMT 2023). We participate in all machine translation tasks, including five bilingual …","url":["https://link.springer.com/chapter/10.1007/978-981-99-7894-6_2"]}
{"year":"2023","title":"HyperGraphDis: Leveraging Hypergraphs for Contextual and Social-Based Disinformation Detection","authors":["N Salamanos, P Leonidou, N Laoutaris, M Sirivianos… - 2023"],"snippet":"In light of the growing impact of disinformation on social, economic, and political landscapes, accurate and efficient identification methods are increasingly critical. This paper introduces HyperGraphDis, a novel approach for detecting disinformation …","url":["https://arxiv.org/pdf/2310.01113"]}
{"year":"2023","title":"HYTREL: Hypergraph-enhanced Tabular Data Representation Learning","authors":["P Chen, S Sarkar, L Lausen, B Srinivasan, S Zha… - arXiv preprint arXiv …, 2023"],"snippet":"… HYTREL pretrained with tables from Wikipedia and Common Crawl could not transfer well to the medical domain PMC dataset. As for the improvement observed from the contrastive objective, the reason could be that contrastive learning that uses …","url":["https://arxiv.org/pdf/2307.08623"]}
{"year":"2023","title":"I-WAS: a Data Augmentation Method with GPT-2 for Simile Detection","authors":["Y Chang, R Zhang, J Pu - arXiv preprint arXiv:2308.04109, 2023"],"snippet":"… For the sentence completion stage, we apply the GPT-2 [35] model, which is trained on a large corpus of novels and common crawl and has 5 billion parameters. The model uses a transformer architecture and consists of a 45-layer decoder with …","url":["https://arxiv.org/pdf/2308.04109"]}
{"year":"2023","title":"ICON: A Linguistically-Motivated Large-Scale Benchmark Indonesian Constituency Treebank","authors":["ES Lim, WQ Leong, NT Nguyen, WM Kng, WC Tjhi… - ACM Transactions on Asian …, 2023"],"snippet":"Constituency parsing is an important task of informing how words are combined to form sentences. While constituency parsing in English has seen significant progress in the last few years, tools for constituency parsing in Indonesian remain few and far …","url":["https://dl.acm.org/doi/pdf/10.1145/3609798"]}
{"year":"2023","title":"Identification and Correction of Grammatical Errors in Ukrainian Texts Based on Machine Learning Technology","authors":["V Lytvyn, P Pukach, V Vysotska, M Vovk, N Kholodna - Mathematics, 2023"],"snippet":"A machine learning model for correcting errors in Ukrainian texts has been developed. It was established that the neural network has the ability to correct simple sentences written in Ukrainian; however, the development of a full-fledged …","url":["https://www.mdpi.com/2128886"]}
{"year":"2023","title":"Identifying and Eliminating CSAM in Generative ML Training Data and Models","authors":["D Thiel - 2023"],"snippet":"… Thisdataset was built by taking a snapshot of the Common Crawl5 repository, downloading images referenced in the HTML, reading the “alt” attributes of the images and using CLIP6 interrogation to discard images that did not sufficiently …","url":["https://stacks.stanford.edu/file/druid:kh752sm9123/ml_training_data_csam_report-2023-12-20.pdf"]}
{"year":"2023","title":"Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey","authors":["V Smith, AS Shamsabadi, C Ashurst, A Weller - arXiv preprint arXiv:2310.01424, 2023"],"snippet":"Rapid advancements in language models (LMs) have led to their adoption across many sectors. Alongside the potential benefits, such models present a range of risks, including around privacy. In particular, as LMs have grown in size, the potential to …","url":["https://arxiv.org/pdf/2310.01424"]}
{"year":"2023","title":"Identifying and predicting stereotype change in large language corpora: 72 groups, 115 years (1900–2015), and four text sources.","authors":["TES Charlesworth, N Sanjeev, ML Hatzenbuehler… - Journal of Personality and …, 2023"],"snippet":"… yearly corpus of New York Times (NYT) articles since 1990; and (d) although not diachronic or time-stamped, the most widely used of any corpus, the Common Crawl (CC), a massive corpus argued to reflect all internet text from the 2000s and before …","url":["https://psycnet.apa.org/record/2024-02028-001"]}
{"year":"2023","title":"Identifying Duplicate Questions Leveraging Recurrent Neural Network","authors":["MB Baby, B Ankhari, M Shajalal, M Atabuzzaman… - Proceedings of the Fourth …, 2023"],"snippet":"Community Question Answering (CQA) forums are the predominant platform where the users can respond to others’ questions and share acquainted insights. The influx of new questions with linguistic expression variability and ambiguity leads to a …","url":["https://link.springer.com/chapter/10.1007/978-981-19-9483-8_28"]}
{"year":"2023","title":"Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space","authors":["F Klubička, V Nedumpozhimana, JD Kelleher - arXiv preprint arXiv:2304.14333, 2023"],"snippet":"The goal of this paper is to learn more about how idiomatic information is structurally encoded in embeddings, using a structural probing method. We repurpose an existing English verbal multi-word expression (MWE) dataset to suit the probing …","url":["https://arxiv.org/pdf/2304.14333"]}
{"year":"2023","title":"If I Say the Word Out Loud, It Will Be More Real","authors":["J Claus, Y Schütte"],"snippet":"… The training set for GPT-3 was a filtered version of the Common Crawl dataset, developed by training a classifier to pick out those documents most similar to the ones used in GPT-2’s training data, ie documents linked to from Reddit, plus …","url":["https://www.transcript-open.de/pdf_chapter/bis%206699/9783839466605/9783839466605-010.pdf"]}
{"year":"2023","title":"Iimas-unam team entry: Transformers adapters for the sentiment analysis rest-mex 2023","authors":["EY Baez-Reyes, I Barrón-Jiménez, H Becerril-Pizarro… - IberLEF@ SEPLN, 2023"],"snippet":"… The transformers model we used is the \"xlm-roberta-base\" model, which is pre-trained with 2.5 TB of data filtered by CommonCrawl. And as an adapter and fine-tuned an adapter. When training a pre-trained model of Huggingface, the first thing we did …","url":["https://ceur-ws.org/Vol-3496/restmex-paper9.pdf"]}
{"year":"2023","title":"Image Synthesis from Themes Captured in Poems using Latent Diffusion Models","authors":["M Virmani, AM Michael, M Pathak, KS Pai, VRB Prasad - 2023 2nd International …, 2023"],"snippet":"… Additionally, MUSS offers an approach that does not require labelled data and uses semantic sentence embeddings to mine paraphrase data from Common Crawl in any language. As a result, MUSS can shorten phrases in any language without …","url":["https://ieeexplore.ieee.org/abstract/document/10141274/"]}
{"year":"2023","title":"Imitating Task and Motion Planning with Visuomotor Transformers","authors":["M Dalal, A Mandlekar, C Garrett, A Handa… - arXiv preprint arXiv …, 2023"],"snippet":"… Large models at the scale of billions of parameters, trained on massive corpi such as Common Crawl, WebText2 [2], JFT-300M [3] and LAION-5B [4], exhibit powerful capabilities. These models can write coherently [2…","url":["https://arxiv.org/pdf/2305.16309"]}
{"year":"2023","title":"Impact and development of an Open Web Index for open web search","authors":["M Granitzer, S Voigt, NA Fathima, M Golasowski… - Journal of the Association …, 2023"],"snippet":"Web search is a crucial technology for the digital economy. Dominated by a few gatekeepers focused on commercial success, however, web publishers have to optimize their content for these gatekeepers, resulting in a closed ecosystem of …","url":["https://asistdl.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/asi.24818"]}
{"year":"2023","title":"Impact of ChatGPT on Interdisciplinary Nursing Education and Research","authors":["H Miao, H Ahn - Asian/Pacific Island Nursing Journal, 2023"],"snippet":"… To train GPT-3, which laid the foundation for ChatGPT, the 2016-2019 Common Crawl data set [6] of 45 TB of compressed plain text was used. Nowadays the data set used for training ChatGPT consists of more than 145 million dialogues scraped …","url":["https://apinj.jmir.org/2023/1/e48136/"]}
{"year":"2023","title":"Impact of Transformers on Multilingual Fake News Detection for Tamil and Malayalam","authors":["RILA Hariharan, M Anand Kumar - Speech and Language Technologies for Low …, 2023"],"snippet":"… XLM-RoBERTa is a multilingual RoBERTa model, an improved version of BERT, and pre-trained on 2.5 TB of filtered CommonCrawl data containing 100 languages. … They trained on monolingual data too, which are publicly available corpora from …","url":["https://link.springer.com/chapter/10.1007/978-3-031-33231-9_13"]}
{"year":"2023","title":"Implications of the Convergence of Language and Vision Model Geometries","authors":["J Li, Y Kementchedjhieva, A Søgaard - arXiv preprint arXiv:2302.06555, 2023"],"snippet":"Large-scale pretrained language models (LMs) are said to ``lack the ability to connect [their] utterances to the world'' (Bender and Koller, 2020). If so, we would expect LM representations to be unrelated to representations in computer vision …","url":["https://arxiv.org/pdf/2302.06555"]}
{"year":"2023","title":"Implicit information extraction from news stories","authors":["H Kydlíček - 2023"],"snippet":"… We used Common Crawl2 as a data source, as crawling live websites would be infeasible. For extraction, we developed a custom tool C’monCrawl3, which allows end-to-end extraction of Common Crawl data. We then deployed it in distributed …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/183054/130358961.pdf?sequence=1"]}
{"year":"2023","title":"Improvements in Language Modeling, Voice Activity Detection, and Lexicon in OpenASR21 Low Resource Languages","authors":["V Gupta, G Boulianne - International Conference on Speech and Computer, 2023"],"snippet":"OpenASR21 evaluation was on 15 low resource languages and 3 case sensitive languages. During the evaluation, participants got significant reduction in word error rates (WER) with text downloaded from the internet for only the case sensitive …","url":["https://link.springer.com/chapter/10.1007/978-3-031-48312-7_6"]}
{"year":"2023","title":"Improving accuracy of GPT-3/4 results on biomedical data using a retrieval-augmented language model","authors":["D Soong, S Sridhar, H Si, JS Wagner, ACC Sá, CY Yu… - arXiv preprint arXiv …, 2023"],"snippet":"… Popular LLMs with billions of parameters such as GPT-3 [4] , PaLM [15], OPT [16], and LLaMA [17] are typically trained on vast amounts of information collected from the Internet (eg the Common Crawl dataset [18]) and capture a diverse range of …","url":["https://arxiv.org/pdf/2305.17116"]}
{"year":"2023","title":"Improving Bug Severity Prediction with Domain-Specific Representation Learning","authors":["Y Wei, C Zhang, T Ren - IEEE Access, 2023"],"snippet":"… Typically, these language models are trained on colossal datasets, such as Wikipedia or Common Crawl, which facilitates their understanding of the intricacies and complexities of natural language. Once trained, these models can be fine-tuned …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10131903.pdf"]}
{"year":"2023","title":"Improving Cascaded Systems in Spoken Language Processing","authors":["Y Lu - 2023"],"snippet":"Spoken language processing encompasses a broad range of speech production and perception tasks. One of the central challenges in building spoken language systems is the lack of end-to-end training corpora. For example in spoken language …","url":["https://www.repository.cam.ac.uk/bitstream/handle/1810/348309/thesis_digital.pdf?sequence=3"]}
{"year":"2023","title":"Improving CLIP Training with Language Rewrites","authors":["L Fan, D Krishnan, P Isola, D Katabi, Y Tian - arXiv preprint arXiv:2305.20088, 2023"],"snippet":"Contrastive Language-Image Pre-training (CLIP) stands as one of the most effective and scalable methods for training transferable vision models using paired image and text data. CLIP models are trained using contrastive loss, which typically relies …","url":["https://arxiv.org/pdf/2305.20088"]}
{"year":"2023","title":"Improving Domain-Specific Retrieval by NLI Fine-Tuning","authors":["R Dušek, A Wawer, C Galias, L Wojciechowska - arXiv preprint arXiv:2308.03103, 2023"],"snippet":"The aim of this article is to investigate the fine-tuning potential of natural language inference (NLI) data to improve information retrieval and ranking. We demonstrate this for both English and Polish languages, using data from one of the largest Polish …","url":["https://arxiv.org/pdf/2308.03103"]}
{"year":"2023","title":"Improving Gender-Related Fairness in Sentence Encoders: A Semantics-Based Approach","authors":["T Dolci, F Azzalini, M Tanelli - Data Science and Engineering, 2023"],"snippet":"… Finally, as underlying word-level representations, we select the biggest and more powerful GloVe model available, trained on Common Crawl 840B. Footnote 5 For the retraining, we used a Linux machine with Ubuntu 18.04, 78GB of RAM and a …","url":["https://link.springer.com/article/10.1007/s41019-023-00211-0"]}
{"year":"2023","title":"Improving Generalization of Adapter-Based Cross-lingual Transfer with Scheduled Unfreezing","authors":["CC Liu, J Pfeiffer, I Vulić, I Gurevych - arXiv preprint arXiv:2301.05487, 2023"],"snippet":"Standard fine-tuning of language models typically performs well on in-distribution data, but suffers with generalization to distribution shifts. In this work, we aim to improve generalization of adapter-based cross-lingual task transfer where such …","url":["https://arxiv.org/pdf/2301.05487"]}
{"year":"2023","title":"Improving Log-Based Anomaly Detection by Pre-Training Hierarchical Transformers","authors":["S Huang, Y Liu, C Fung, H Wang, H Yang, Z Luan - IEEE Transactions on Computers, 2023"],"snippet":"… For example, LogRobust [8] leverages word vectors pre-trained on the Common Crawl Corpus [10] dataset to extract the log event’s semantic information and transforms each log event into a semantic vector. It then utilizes an attention-based …","url":["https://ieeexplore.ieee.org/abstract/document/10070784/"]}
{"year":"2023","title":"Improving Low-Resource Languages in Pre-Trained Multilingual Language Models","authors":["V Hangya, HS Saadi, A Fraser - Proceedings of the 2022 Conference on Empirical …, 2022"],"snippet":"… However, multilingual LMs mainly focus on high resource languages, eg, mBERT supports the top 104 languages based on Wikipedia sizes, while XLM-R supports the top 100 based on CommonCrawl data. Additionally, many of these languages …","url":["https://aclanthology.org/2022.emnlp-main.822.pdf"]}
{"year":"2023","title":"Improving Machine Translation in the E-commerce Luxury Space. A case study","authors":["JM De-la-Torre-Vilariño, JL García-Mendoza… - Proceedings of the 24th …, 2023"],"snippet":"This case study presents a Multilingual e-commerce Project, which principal aim is to create an improved system that translates product titles and descriptions, plus other content in multiple languages. The project consisted of two main phases; a …","url":["https://aclanthology.org/2023.eamt-1.43.pdf"]}
{"year":"2023","title":"Improving Multiclass Classification of Fake News Using BERT-Based Models and ChatGPT-Augmented Data","authors":["E Shushkevich, M Alexandrov, J Cardiff - Inventions, 2023"],"snippet":"Given the widespread accessibility of content creation and sharing, false information proliferation is a growing concern. Researchers typically tackle fake news detection (FND) in specific topics using binary classification. Our study addresses a more practical …","url":["https://www.mdpi.com/2411-5134/8/5/112"]}
{"year":"2023","title":"Improving Multimodal Datasets with Image Captioning","authors":["T Nguyen, SY Gadre, G Ilharco, S Oh, L Schmidt - arXiv preprint arXiv:2307.10350, 2023"],"snippet":"… We also work with raw Common Crawl data instead of preprocessed datasets to study the trade-offs between raw and generated captions in a systematic manner. Finally, Gadre et al. [18] introduces DataComp, a benchmark for designing better pre-training …","url":["https://arxiv.org/pdf/2307.10350"]}
{"year":"2023","title":"Improving Natural Language Inference in Arabic using Transformer Models and Linguistically Informed Pre-Training","authors":["MMSA Deen, M Pielka, J Hees, BS Abdou, R Sifa - arXiv preprint arXiv:2307.14666, 2023"],"snippet":"This paper addresses the classification of Arabic text data in the field of Natural Language Processing (NLP), with a particular focus on Natural Language Inference (NLI) and Contradiction Detection (CD). Arabic is considered a resource-poor language …","url":["https://arxiv.org/pdf/2307.14666"]}
{"year":"2023","title":"Improving network intrusion detection applying hybrid machine learning algorithms","authors":["K Čiurlienė, D Stankevičius - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:147315981/147315981.pdf"]}
{"year":"2023","title":"Improving predictive models for rate of penetration in real drilling operations through transfer learning","authors":["FJ Pacis, A Ambrus, S Alyaev, R Khosravanian… - Journal of Computational …, 2023"],"snippet":"The rate of penetration (ROP) is a key performance indicator in the oil and gas drilling industry as it directly translates to cost savings and emission reductions. A prerequisite for a drilling optimization algorithm is a predictive model that provides …","url":["https://www.sciencedirect.com/science/article/pii/S1877750323001606"]}
{"year":"2023","title":"Improving Subword Tokenization Methods for Multilingual Models","authors":["J Balhar"],"snippet":"… This unlabeled, multilingual dataset was created from the Common Crawl corpus using an automatic pipeline. The data was deduplicated and languageidentified. Then for each monolingual corpus the data was filtered using KneserNey language …","url":["https://jirkabalhar.cz/diplomka/diplomka.pdf"]}
{"year":"2023","title":"Improving Word Embedding Using Variational Dropout","authors":["Z Albujasim, D Inkpen, X Han, Y Guo - The International FLAIRS Conference …, 2023"],"snippet":"Pre-trained word embeddings are essential in natural language processing (NLP). In recent years, many post-processing algorithms have been proposed to improve the pre-trained word embeddings. We present a novel method-Orthogonal Auto …","url":["https://journals.flvc.org/FLAIRS/article/download/133326/137934"]}
{"year":"2023","title":"Improving Word Sense Disambiguation in Neural Machine Translation with Salient Document Context","authors":["E Rippeth, M Carpuat, K Duh, M Post - arXiv preprint arXiv:2311.15507, 2023"],"snippet":"Lexical ambiguity is a challenging and pervasive problem in machine translation (\\mt). We introduce a simple and scalable approach to resolve translation ambiguity by incorporating a small amount of extra-sentential context in neural \\mt. Our approach …","url":["https://arxiv.org/pdf/2311.15507"]}
{"year":"2023","title":"In search of founding era registers: automatic modeling of registers from the corpus of Founding Era American English","authors":["L Repo, B Hashimoto, V Laippala - Digital Scholarship in the Humanities, 2023"],"snippet":"Registers are situationally defined text varieties, such as letters, essays, or news articles, that are considered to be one of the most important predictors of linguistic variation. Often historical databases of language lack register information, which …","url":["https://academic.oup.com/dsh/advance-article/doi/10.1093/llc/fqad049/7293015"]}
{"year":"2023","title":"In What Languages are Generative Language Models the Most Formal? Analyzing Formality Distribution across Languages","authors":["A Ersoy, G Vizcarra, TT Mayeesha, B Muller - arXiv preprint arXiv:2302.12299, 2023"],"snippet":"… BLOOM was trained from a collection of multiple sources such as Huggingface datasets, Github code, and Web Common Crawl. The data sources were then preprocessed to reduce non-natural language and anonymize personal identifiable …","url":["https://arxiv.org/pdf/2302.12299"]}
{"year":"2023","title":"In-Context Pretraining: Language Modeling Beyond Document Boundaries","authors":["W Shi, S Min, M Lomeli, C Zhou, M Li, V Lin, NA Smith… - arXiv preprint arXiv …, 2023"],"snippet":"… For example, less than 5% of documents in CommonCrawl have longer than 2k tokens. In this work, we focus on constructing meaningful long-context data, making language models better leverage its context-window. Our sorted data can be used …","url":["https://arxiv.org/pdf/2310.10638"]}
{"year":"2023","title":"IN-ORDER TRANSITION-BASED PARSING FOR VIETNAMESE","authors":["J Bauer, H Bui, V Thai, C Manning - Journal of Computer Science and Cybernetics, 2023"],"snippet":"In this paper, we implement a general neural constituency parser based on an in-order parser. We apply this parser to the VLSP 2022 Vietnamese treebank, obtaining a test score of. 8393 F1, top of the private test leaderboard. Earlier versions of the …","url":["https://vjs.ac.vn/index.php/jcc/article/download/18363/2543255143"]}
{"year":"2023","title":"Incorporating Natural Language Processing into Virtual Assistants: An Intelligent Assessment Strategy for Enhancing Language Comprehension","authors":["F Antonius, PR Alapati, M Ritonga, I Patra… - International Journal of …, 2023"],"snippet":"… The process starts with the selection of diverse pretraining datasets, including the multilingual Colossal Clean Common Crawl (mC4), CC100 dataset, and Wikipedia data. These datasets encompass various domains, languages, and tones …","url":["https://search.proquest.com/openview/8a5aff1d8b440faaecab2bed684db6c1/1?pq-origsite=gscholar&cbl=5444811"]}
{"year":"2023","title":"IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages","authors":["J Gala, PA Chitale, R AK, S Doddapaneni, V Gumma… - arXiv preprint arXiv …, 2023"],"snippet":"India has a rich linguistic landscape with languages from 4 major language families spoken by over a billion people. 22 of these languages are listed in the Constitution of India (referred to as scheduled languages) are the focus of this work. Given the …","url":["https://arxiv.org/pdf/2305.16307"]}
{"year":"2023","title":"IndiSocialFT: Multilingual Word Representation for Indian languages in code-mixed environment","authors":["S Kumar, R Sanasam, S Nandi - Findings of the Association for Computational …, 2023"],"snippet":"The increasing number of Indian language users on the internet necessitates the development of Indian language technologies. In response to this demand, our paper presents a generalized representation vector for diverse text characteristics …","url":["https://aclanthology.org/2023.findings-emnlp.252.pdf"]}
{"year":"2023","title":"IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems","authors":["MDA Kautsar, RK Nurdini, S Cahyawijaya, GI Winata… - arXiv preprint arXiv …, 2023"],"snippet":"… Specifically, we incorporate common crawl4 English and Indonesian fastText word vectors for monolingual English and Indonesian experiment settings respectively. Meanwhile, we use bilingual English-Indonesian word vectors (Conneau et al.…","url":["https://arxiv.org/pdf/2311.00958"]}
{"year":"2023","title":"Influence of the duration of training a deep neural network model on the quality of text summarization task","authors":["A Gryaznov, R Rybka, I Moloshnikov, A Selivanov… - AIP Conference …, 2023"],"snippet":"In this paper we apply the generative deep learning language model to text summarization task. Because such large language models require a lot of resources to train, it is interesting to study how much long training affects the final result and at …","url":["https://pubs.aip.org/aip/acp/article/2849/1/400006/2909197"]}
{"year":"2023","title":"Information Access Using Neural Networks For Diverse Domains And Sources","authors":["Y Xie - 2023"],"snippet":"The ever-increasing volume of web-based documents poses a challenge in efficiently accessing specialized knowledge from domain-specific sources, requiring a profound understanding of the domain and substantial comprehension effort …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19837/Xie_Yuqing.pdf?sequence=3&isAllowed=y"]}
{"year":"2023","title":"Information Extraction and Knowledge Graph Development for Manufacturing Science Domain using Natural Language Processing.","authors":["A Kumar - 2023"],"snippet":"KUMAR, AMAN. Information Extraction and Knowledge Graph Development for Manufacturing Science Domain using Natural Lang Page 1 ABSTRACT KUMAR, AMAN. Information Extraction and Knowledge Graph Development for …","url":["https://repository.lib.ncsu.edu/bitstream/handle/1840.20/40758/etd.pdf?sequence=1"]}
{"year":"2023","title":"Information Extraction from Polish Radiology Reports using Language Models","authors":["A Obuchowski, B Klaudel, P Jasik - Proceedings of the 9th Workshop on Slavic …, 2023"],"snippet":"… All the models were pre-trained using a Polish subset of the Common Crawl corpus. The model’s pre-training details are shown in (Dadas … 2019) embeddings for the Polish language trained on the Polish part of the Common Crawl dataset …","url":["https://aclanthology.org/2023.bsnlp-1.14.pdf"]}
{"year":"2023","title":"Information resource management researchers' thinking about the opportunities and challenges of AIGC","authors":["Z ZHANG, Z Jianxun, XIA Cuijuan, W Dongbo… - Journal of Library and …, 2023"],"snippet":"With the explosive popularity of ChatGPT and the development of AI generated content (AIGC), the new generation of artificial intelligence (AI) technology has triggered people's imagination and discussion about the production mode of digital …","url":["https://search.proquest.com/openview/c6d31b7b2204519d42c799e9faeab34b/1?pq-origsite=gscholar&cbl=6524071"]}
{"year":"2023","title":"infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information","authors":["J Kim, Y Kim, K de Langis, J Shin, D Kang - arXiv preprint arXiv:2305.19344, 2023"],"snippet":"The success of NLP systems often relies on the availability of large, high-quality datasets. However, not all samples in these datasets are equally valuable for learning, as some may be redundant or noisy. Several methods for characterizing …","url":["https://arxiv.org/pdf/2305.19344"]}
{"year":"2023","title":"INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Large Language Models","authors":["HK Renduchintala, K Killamsetty, S Bhatia, M Aggarwal… - arXiv preprint arXiv …, 2023"],"snippet":"A salient characteristic of large pre-trained language models (PTLMs) is a remarkable improvement in their generalization capability and emergence of new capabilities with increasing model capacity and pre-training dataset size …","url":["https://arxiv.org/pdf/2305.06677"]}
{"year":"2023","title":"Inria-ALMAnaCH at WMT 2022: Does Transcription Help Cross-Script Machine Translation?","authors":["J Alabi, L Nishimwe, B Muller, C Rey, B Sagot… - Proceedings of the Seventh …, 2022"],"snippet":"This paper describes the Inria ALMAnaCH team submission to the WMT 2022 general translation shared task. Participating in the language directions {cs, ru, uk}→ en and cs↔ uk, we experiment with the use of a dedicated Latin-script transcription …","url":["https://aclanthology.org/2022.wmt-1.15.pdf"]}
{"year":"2023","title":"Insincere Questions Classification Using CNN with Increased Vocabulary Coverage of GloVe Embedding","authors":["S Mishra, N Kumar - Journal of The Institution of Engineers (India): Series B, 2023"],"snippet":"… word embedding used in training the model is the GloVe word embedding from Stanford NLP [9], the GloVe stands for “Global Vectors for Word Representation”, it is a pre-trained embedding and has different options, so for this study, the authors …","url":["https://link.springer.com/article/10.1007/s40031-023-00858-3"]}
{"year":"2023","title":"Instance-Based Domain Adaptation for Improving Terminology Translation","authors":["P Nayak, J Kelleher, R Haque, A Way - … of Machine Translation Summit XIX, Vol. 1 …, 2023"],"snippet":"Terms are essential indicators of a domain, and domain term translation is dealt with priority in any translation workflow. Translation service providers who use machine translation (MT) expect term translation to be unambiguous and consistent with the …","url":["https://aclanthology.org/2023.mtsummit-research.19.pdf"]}
{"year":"2023","title":"InstructIE: A Chinese Instruction-based Information Extraction Dataset","authors":["H Gui, J Zhang, H Ye, N Zhang - arXiv preprint arXiv:2305.11527, 2023"],"snippet":"We introduce a new Information Extraction (IE) task dubbed Instruction-based IE, which aims to ask the system to follow specific instructions or guidelines to extract information. To facilitate research in this area, we construct a dataset called InstructIE …","url":["https://arxiv.org/pdf/2305.11527"]}
{"year":"2023","title":"Instruction-tuning Aligns LLMs to the Human Brain","authors":["KL Aw, S Montariol, B AlKhamissi, M Schrimpf… - arXiv preprint arXiv …, 2023"],"snippet":"… T5 models are encoder-decoder LLMs pretrained on the Colossal Common Crawl Corpus (C4), a corpus of 356 billion tokens, using a masked infilling objective, and then further finetuned on multi-task mixture of unsupervised and supervised …","url":["https://arxiv.org/pdf/2312.00575"]}
{"year":"2023","title":"InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining","authors":["B Wang, W Ping, L McAfee, P Xu, B Li, M Shoeybi… - arXiv preprint arXiv …, 2023"],"snippet":"Pretraining auto-regressive large language models (LLMs) with retrieval demonstrates better perplexity and factual accuracy by leveraging external databases. However, the size of existing pretrained retrieval-augmented LLM is still …","url":["https://arxiv.org/pdf/2310.07713"]}
{"year":"2023","title":"Integrating artificial intelligence-based methods into qualitative research in physics education research: A case for computational grounded theory","authors":["P Tschisgale, P Wulff, M Kubsch - Physical Review Physics Education Research, 2023"],"snippet":"[This paper is part of the Focused Collection on Qualitative Methods in PER: A Critical Examination.] Qualitative research methods have provided key insights in physics education research (PER) by drawing on non-numerical data such as text or …","url":["https://link.aps.org/pdf/10.1103/PhysRevPhysEducRes.19.020123"]}
{"year":"2023","title":"Integrating Offline Reinforcement Learning with Transformers for Sequential Recommendation","authors":["X Xi, Y Zhao, Q Liu, L Ouyang, Y Wu - arXiv preprint arXiv:2307.14450, 2023"],"snippet":"We consider the problem of sequential recommendation, where the current recommendation is made based on past interactions. This recommendation task requires efficient processing of the sequential data and aims to provide …","url":["https://arxiv.org/pdf/2307.14450"]}
{"year":"2023","title":"Intelligent Phishing Website Detection before and after Multiple Informative Feature Selection Techniques: Machine Learning Approach","authors":["K Adane, B Beyene, M Abebe - International Journal of Information, 2024"],"snippet":"Individuals and Organizations that rely on the Internet for communication, collaboration, and daily tasks regularly encounter security and privacy issues unless interventions of intelligent Cybersecurity defense systems have been made to …","url":["https://ijism.ricest.ac.ir/article_709483_9565ffb496f4a333610af887bfea03ca.pdf"]}
{"year":"2023","title":"Intent Detection in Urdu Queries using Fine-tuned BERT models","authors":["S Shams, B Sadia, M Aslam - 2022 16th International Conference on Open Source …, 2022"],"snippet":"User's intent detection provides essential cues in query understanding and accurate information retrieval through search engines and task-oriented dialogue systems. Intent detection from user queries is challenging due to short query length and lack …","url":["https://ieeexplore.ieee.org/abstract/document/10016834/"]}
{"year":"2023","title":"Interactive Natural Language Processing","authors":["Z Wang, G Zhang, K Yang, N Shi, W Zhou, S Hao… - arXiv preprint arXiv …, 2023"],"snippet":"… 2008), PubMed Corpus4, and CommonCrawl Corpus5, among others. Most previous research has focused on corpus knowledge due to its controllability and efficiency. RetrievalAugmented Language Models (Guu et … 4https://pubmed.ncbi.nlm.nih.gov …","url":["https://arxiv.org/pdf/2305.13246"]}
{"year":"2023","title":"Interactive writing systems and why small (er) could be more beautiful","authors":["I Olatunji"],"snippet":"ABSTRACT Machine learning models can support human creativity, including tasks such as writing. This position paper explorers and critiques the design of writing systems based on big data. The paper proposes small data as way to think about …","url":["https://cdn.glitch.global/d058c114-3406-43be-8a3c-d3afff35eda2/paper8_2023.pdf"]}
{"year":"2023","title":"Intercity networks and urban performance: a geographical text mining approach","authors":["W Tongjing, E Meijers, Z Bao, H Wang - International Journal of Urban Sciences, 2023"],"snippet":"… While it is possible to search for toponym occurrences using a search engine like google, results returned are vulnerable to bias (Meijers & Peris, Citation2019), and like Meijers and Peris we prefer using corpora from the CommonCrawl Archive of …","url":["https://www.tandfonline.com/doi/pdf/10.1080/12265934.2023.2253193"]}
{"year":"2023","title":"Interconnecting Advanced Networks with AI Applications","authors":["A Luntovskyy - Preprints of Position Papers of the 18th Conference on …, 2023"],"snippet":"… org as a text’s source can also be specified as the so-called C4 (Common Crawl Cultural Context). Furthermore, the sources of texts can be differentiated as follows: search engines, online forums and communities, social media, blogs, newspapers …","url":["https://annals-csis.org/proceedings/2023/pliks/position.pdf#page=83"]}
{"year":"2023","title":"INTERPRETING THE RELEVANCE OF READABILITY PREDICTION FEATURES","authors":["S Berrichi, N Nassiri, A Mazroui, A Lakhouaja - Jordanian Journal of Computers and …, 2023"],"snippet":"… from “Common Crawl” and a dump of Arabic Wikipedia totaling 8.2 billion words. Different pretrained BERT models are used. We have selected in this study, the bert-base-Arabic model. 3) XLM-R [29]: is a multi-lingual version of BERT model, trained on “Common …","url":["https://search.proquest.com/openview/1ac2e34f30c82362dd25d671ecfad14a/1?pq-origsite=gscholar&cbl=5500744"]}
{"year":"2023","title":"Into the LAION's Den: Investigating Hate in Multimodal Datasets","authors":["A Birhane, S Han, V Boddeti, S Luccioni - Thirty-seventh Conference on Neural …, 2023"],"snippet":"… -2B-en are extracted from the Common Crawl dataset, we hypothesize that during the race to expand the dataset to 5 billion samples, the dataset scraping module might have sampled from the lower-quality sub-parts of the Common Crawl at a rate …","url":["https://openreview.net/pdf?id=6URyQ9QhYv"]}
{"year":"2023","title":"Intriguing Properties of Quantization at Scale","authors":["A Ahmadian, S Dash, H Chen, B Venkitesh, S Gou… - arXiv preprint arXiv …, 2023"],"snippet":"Emergent properties have been widely adopted as a term to describe behavior not present in smaller models but observed in larger models. Recent work suggests that the trade-off incurred by quantization is also an emergent property, with sharp drops …","url":["https://arxiv.org/pdf/2305.19268"]}
{"year":"2023","title":"Introducing UberText 2.0: a corpus of modern Ukrainian at scale","authors":["D Chaplynskyi - Proceedings of the Second Ukrainian Natural …, 2023"],"snippet":"This paper addresses the need for massive corpora for a low-resource language and presents the publicly available UberText 2.0 corpus for the Ukrainian language and discusses the methodology of its construction. While the collection and …","url":["https://aclanthology.org/2023.unlp-1.1.pdf"]}
{"year":"2023","title":"Introduction to ChatGPT: A new revolution of artificial intelligence with machine learning algorithms and cybersecurity","authors":["MA Hadi, MN Abdulredha, E Hasan"],"snippet":"ChatGPTis an innovative natural language processing (NLP) technology developed by OpenAI. It has revolutionized humancomputer interactions by utilizing Machine Learning (ML) and Deep Learning (DL) algorithms. ChatGPT generates a …","url":["https://www.researchgate.net/profile/Mohammed-Najm/publication/376391507_Introduction_to_ChatGPT_A_new_revolution_of_artificial_intelligence_with_machine_learning_algorithms_and_cybersecurity/links/6576a230cbd2c535ea157e98/Introduction-to-ChatGPT-A-new-revolution-of-artificial-intelligence-with-machine-learning-algorithms-and-cybersecurity.pdf"]}
{"year":"2023","title":"Investigating Biases in Rules Extracted from Language Models","authors":["SM Blum - 2023"],"snippet":"We investigate an approach for extracting occupational gender bias in the form of logical rules from Large Language Models (LLM)s based on Angluin's exact learning model with membership and equivalence queries to an oracle. In our …","url":["https://bora.uib.no/bora-xmlui/bitstream/handle/11250/3086287/Master_Thesis_Sophie_Blum.pdf?sequence=1"]}
{"year":"2023","title":"Investigating parallelograms inside word embedding space using various analogy test sets in various languages","authors":["R Fam, Y Lepage"],"snippet":"The idea of using analogy to assess the quality of word embedding spaces implies the existence of parallelograms between the four terms of an analogy. We investigate the presence of analogy parallelograms in various word embedding …","url":["https://www.anlp.jp/proceedings/annual_meeting/2023/pdf_dir/P3-3.pdf"]}
{"year":"2023","title":"Investigating the Extent and Usability of Webtext Available in South Africa's Official Languages","authors":["F de Wet, R Eiselen, E Schillack, M Puttkammer - Southern African Conference for …, 2023"],"snippet":"… The Common Crawl (CC) data set is likely the largest text data set currently available consisting of (bi-)monthly crawls of the web, and is … Part of the common crawl collection process is language identification to categorise the predominant …","url":["https://link.springer.com/chapter/10.1007/978-3-031-49002-6_9"]}
{"year":"2023","title":"Investigating Vision Foundational Models for Tactile Representation Learning","authors":["B Zandonati, R Wang, R Gao, Y Wu - arXiv preprint arXiv:2305.00596, 2023"],"snippet":"… In particular, foundational models [11] are trained on massive datasets such as ImageNet [12] and CommonCrawl [13] to derive general representational knowledge, which can be specialized to diverse downstream tasks, such as semantic …","url":["https://arxiv.org/pdf/2305.00596"]}
{"year":"2023","title":"Investigation of quantum-inspired modelling in interactive search based on information foraging theory","authors":["AK Jaiswal - 2023"],"snippet":"This thesis investigates the use of the mathematical formalism of quantum mechanics for modelling users’ information needs from the viewpoint of Information Foraging Theory (IFT). IFT has been successfully applied to model user behaviours …","url":["https://uobrep.openrepository.com/bitstream/handle/10547/625945/JAISWAL%20Amit%201808389%20QUARTZ%20FULL%20REPOSITORY%20COPY.pdf?sequence=1"]}
{"year":"2023","title":"IOL Research Machine Translation Systems for WMT23 General Machine Translation Shared Task","authors":["W Zhang, Z Yan, Q Deng, J Cai, H Mao - Proceedings of the Eighth Conference on …, 2023"],"snippet":"This paper describes the IOL Research team’s submission systems for the WMT23 general machine translation shared task. We participated in two language translation directions, including English→ Chinese and Chinese→ English. Our final …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.19.pdf"]}
{"year":"2023","title":"IPARO: INTERPLANETARY ARCHIVAL RECORD OBJECT FOR DECENTRALIZED WEB ARCHIVING AND REPLAY","authors":["S Alam - iPRES 2023, 2023"],"snippet":"We proposed a decentralized version tracking system using the existing primitives of IPFS and IPNS. While our description talks primarily about archived web pages, we proposed the concept of IPMT and namespacing so that it can be used in other …","url":["https://www.ideals.illinois.edu/items/128294/bitstreams/428953/object"]}
{"year":"2023","title":"Irreducible Curriculum for Language Model Pretraining","authors":["S Fan, M Jaggi - arXiv preprint arXiv:2310.15389, 2023"],"snippet":"… 5, IRREDUCIBLE CURRICULUM reduce the validation perplexity on 4 domains (C4, CommonCrawl, Book and Wikipedia), while showing the … Figure 4 shows that most of the globally top-ranked samples are from Wikipedia, C4 and CommonCrawl …","url":["https://arxiv.org/pdf/2310.15389"]}
{"year":"2023","title":"Is GPT-3 all you need for low-data discovery in chemistry?","authors":["KM Jablonka, P Schwaller, A Ortega-Guerrero, B Smit - 2023"],"snippet":"… The version of GPT-3 we utilized in this work has been trained on data up to Oct 2019 that mostly comes from web scraping (Common Crawl47 and WebText48) along with books corpora and Wikipedia. Structured datasets, however, have not …","url":["https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/63eb5a669da0bc6b33e97a35/original/is-gpt-3-all-you-need-for-low-data-discovery-in-chemistry.pdf"]}
{"year":"2023","title":"IS IT POSSIBLE TO RE-EDUCATE ROBERTA? EXPERT-DRIVEN MACHINE LEARNING FOR PUNCTUATION CORRECTION","authors":["JMH ŽIŽKOVÁ, AFJAN ŠVEC - JAZYKOVEDNÝ ČASOPIS"],"snippet":"… As the training data set used for fine-tuning, we used 10 GB of raw text extracted from the Czech CommonCrawl data set. Because RoBERTa’s output is related to input tokens (not words), we assigned the target label (‟,” for comma,“0” for no …","url":["https://www.researchgate.net/profile/Michal-Mistecky-2/publication/374698410_Appellativization_of_Proper_Names_-_In_the_Perspective_of_Corpus_Analysis/links/6529c94a06bdd619c48c15ed/Appellativization-of-Proper-Names-In-the-Perspective-of-Corpus-Analysis.pdf#page=359"]}
{"year":"2023","title":"Is More Always Better? Testing the Addition Bias for German Language Statistics","authors":["S Wolfer - Cognitive Science, 2023"],"snippet":"This replication study aims to investigate a potential bias toward addition in the German language, building upon previous findings of Winter and colleagues who identified a similar bias in English. Our results confirm a bias in word frequencies …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/cogs.13339"]}
{"year":"2023","title":"Issues Surrounding the Use of ChatGPT in Similar Languages: The Case of Malay and Indonesian","authors":["H Nomoto - Malay"],"snippet":"We report a problem that one faces when using ChatGPT in similar languages, taking Malay and Indonesian as examples: ChatGPT often responds to prompts in Malay (the language with fewer speakers) in Indonesian (the language with more …","url":["http://www.afnlp.org/conferences/ijcnlp2023/proceedings/main-short/cdrom/pdf/2023.ijcnlp-short.9.pdf"]}
{"year":"2023","title":"Its All Graph To Me: Foundational Topology Models with Contrastive Learning on Multiple Domains","authors":["AO Davies, R Green, NS Ajmeri, TM Silva Filho - arXiv preprint arXiv:2311.03976, 2023"],"snippet":"Abstract Representations and embeddings of graph data have been essential in many domains of research. The principle benefit of learning such representations is that the pretrained model can be fine-tuned on smaller datasets where data or labels …","url":["https://arxiv.org/pdf/2311.03976"]}
{"year":"2023","title":"IussNets at DisCo-Tex: A fine-tuned approach to coherence","authors":["E Zanoli, M Barbini, C Chesi - Proceedings of the Eighth Evaluation Campaign of …, 2023"],"snippet":"We present our submission to the DisCoTex shared task of the EVALITA 2023 evaluation campaign, which focuses on modeling discourse coherence for Italian texts. We highlight the importance of coherence modeling in natural language …","url":["https://ceur-ws.org/Vol-3473/paper50.pdf"]}
{"year":"2023","title":"Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models","authors":["N Sengupta, SK Sahu, B Jia, S Katipomu, H Li, F Koto… - arXiv preprint arXiv …, 2023"],"snippet":"… • Pile-CC: A subset of The Pile dataset, derived from the Common Crawl, a collection of website crawls from 2008 onwards. The dataset includes raw web pages, metadata, and text extractions from diverse domains. Due to the varying …","url":["https://arxiv.org/pdf/2308.16149"]}
{"year":"2023","title":"Jake Glendenning","authors":["IIM LEARNING - AIPLA QUARTERLY JOURNAL, 2023"],"snippet":"… sentence and understand that machine learning models like GPT-3 don't \"read\" like humans do, but rather ingest data sets like Common Crawl, which is made up of many written works … 2020) (explaining the use of the Common Crawl dataset in …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/aiplaqj51&section=5"]}
{"year":"2023","title":"Japanese SimCSE Technical Report","authors":["H Tsukagoshi, R Sasano, K Takeda - arXiv preprint arXiv:2310.19349, 2023"],"snippet":"We report the development of Japanese SimCSE, Japanese sentence embedding models fine-tuned with SimCSE. Since there is a lack of sentence embedding models for Japanese that can be used as a baseline in sentence embedding …","url":["https://arxiv.org/pdf/2310.19349"]}
{"year":"2023","title":"JCoLA: Japanese Corpus of Linguistic Acceptability","authors":["T Someya, Y Sugimoto, Y Oseki - arXiv preprint arXiv:2309.12676, 2023"],"snippet":"Neural language models have exhibited outstanding performance in a range of downstream tasks. However, there is limited understanding regarding the extent to which these models internalize syntactic knowledge, so that various datasets have …","url":["https://arxiv.org/pdf/2309.12676"]}
{"year":"2023","title":"Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents","authors":["M Günther, J Ong, I Mohr, A Abdessalem, T Abel… - arXiv preprint arXiv …, 2023"],"snippet":"Text embedding models have emerged as powerful tools for transforming sentences into fixed-sized feature vectors that encapsulate semantic information. While these models are essential for tasks like information retrieval, semantic clustering, and text …","url":["https://arxiv.org/pdf/2310.19923"]}
{"year":"2023","title":"KASYS at the TREC 2022 NeuCLIR Track","authors":["K Abe, K Shinden, MP Kato"],"snippet":"This paper describes the KASYS team’s participation in the TREC 2022 NeuCLIR track. Our approach is One-for-All, which employs a single multilingual pre-trained language model to retrieve documents of any languages in response to an English …","url":["https://trec.nist.gov/pubs/trec31/papers/KASYS.N.pdf"]}
{"year":"2023","title":"KaustubhSharedTask@ LT-EDI 2023: Homophobia-Transphobia Detection in Social Media Comments with NLPAUG-driven Data Augmentation","authors":["K Lande, R Ponnusamy, PK Kumaresan… - Proceedings of the Third …, 2023"],"snippet":"Our research in Natural Language Processing (NLP) aims to detect hate speech comments specifically targeted at the LGBTQ+ community within the YouTube platform shared task conducted by LTEDI workshop. The dataset provided by the …","url":["https://aclanthology.org/2023.ltedi-1.10.pdf"]}
{"year":"2023","title":"Keyword Embeddings for Query Suggestion","authors":["J Gabín, ME Ares, J Parapar - arXiv preprint arXiv:2301.08006, 2023"],"snippet":"Nowadays, search engine users commonly rely on query suggestions to improve their initial inputs. Current systems are very good at recommending lexical adaptations or spelling corrections to users' queries. However, they often struggle to …","url":["https://arxiv.org/pdf/2301.08006"]}
{"year":"2023","title":"Know Where to Go: Make LLM a Relevant, Responsible, and Trustworthy Searcher","authors":["X Shi, J Liu, Y Liu, Q Cheng, W Lu - arXiv preprint arXiv:2310.12443, 2023"],"snippet":"The advent of Large Language Models (LLMs) has shown the potential to improve relevance and provide direct answers in web searches. However, challenges arise in validating the reliability of generated results and the credibility of contributing …","url":["https://arxiv.org/pdf/2310.12443"]}
{"year":"2023","title":"Knowledge and Pre-trained Language Models: a deep-dive into datasets and external knowledge","authors":["C Lyu - 2023"],"snippet":"Recent years have witnessed the emergence of Pre-trained Language Models (PLMs), such as ELMo, GPT, BERT, XLNet, GPT-3 and InstructGPT [11, 12, 13, 14, 15, 16, 17, 18, 19], which have been widely used in many NLP tasks and have shown superior …","url":["https://www.researchgate.net/profile/Chenyang-Lyu-4/publication/373632826_Knowledge_and_Pre-trained_Language_Models_a_deep-dive_into_datasets_and_external_knowledge/links/64f445b94c70687b8ecbdac9/Knowledge-and-Pre-trained-Language-Models-a-deep-dive-into-datasets-and-external-knowledge.pdf"]}
{"year":"2023","title":"Knowledge Informed Fake News Detection Using Large Language Models","authors":["JJ Benny - 2023"],"snippet":"The spread of false or misleading information as news has been a significant threat to governments, organizations and the economy for a long time. However, it has become more prevalent and influential in recent years due to the growing popularity …","url":["https://search.proquest.com/openview/0041daa59cded0bc477e27a17af5500e/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Knowledge of cultural moral norms in large language models","authors":["A Ramezani, Y Xu - arXiv preprint arXiv:2306.01857, 2023"],"snippet":"Moral norms vary across cultures. A recent line of work suggests that English large language models contain human-like moral biases, but these studies typically do not examine moral variation in a diverse cultural setting. We investigate the extent to …","url":["https://arxiv.org/pdf/2306.01857"]}
{"year":"2023","title":"Knowledge-Based and Generative-AI-Driven Pedagogical Conversational Agents: A Comparative Study of Grice's Cooperative Principles and Trust","authors":["M Wölfel, MB Shirzad, A Reich, K Anderer - Big Data and Cognitive Computing, 2023"],"snippet":"The emergence of generative language models (GLMs), such as OpenAI’s ChatGPT, is changing the way we communicate with computers and has a major impact on the educational landscape. While GLMs have great potential to support education, their …","url":["https://www.mdpi.com/2504-2289/8/1/2"]}
{"year":"2023","title":"KoBigBird-large: Transformation of Transformer for Korean Language Understanding","authors":["K Yang, Y Jang, T Lee, J Seong, H Lee, H Jang, H Lim - arXiv preprint arXiv …, 2023"],"snippet":"This work presents KoBigBird-large, a large size of Korean BigBird that achieves state-of-the-art performance and allows long sequence processing for Korean language understanding. Without further pretraining, we only transform the …","url":["https://arxiv.org/pdf/2309.10339"]}
{"year":"2023","title":"Kosmos-2.5: A Multimodal Literate Model","authors":["T Lv, Y Huang, J Chen, L Cui, S Ma, Y Chang, S Huang… - arXiv preprint arXiv …, 2023"],"snippet":"We present Kosmos-2.5, a multimodal literate model for machine reading of text-intensive images. Pre-trained on large-scale text-intensive images, Kosmos-2.5 excels in two distinct yet cooperative transcription tasks: (1) generating spatially-aware text blocks …","url":["https://arxiv.org/pdf/2309.11419"]}
{"year":"2023","title":"Kosmos-G: Generating Images in Context with Multimodal Large Language Models","authors":["X Pan, L Dong, S Huang, Z Peng, W Chen, F Wei - arXiv preprint arXiv:2310.02992, 2023"],"snippet":"Recent advancements in text-to-image (T2I) and vision-language-to-image (VL2I) generation have made significant strides. However, the generation from generalized vision-language inputs, especially involving multiple images, remains under-explored …","url":["https://arxiv.org/pdf/2310.02992"]}
{"year":"2023","title":"KTRL+ F: Knowledge-Augmented In-Document Search","authors":["H Oh, H Shin, M Ko, H Lee, M Seo - arXiv preprint arXiv:2311.08329, 2023"],"snippet":"We introduce a new problem KTRL+F, a knowledge-augmented in-document search task that necessitates real-time identification of all semantic targets within a document with the awareness of external sources through a single natural query …","url":["https://arxiv.org/pdf/2311.08329"]}
{"year":"2023","title":"Lagniappe: Exploring the Pros and Cons of ChatGPT","authors":["J Daugherty - North Carolina Libraries, 2023"],"snippet":"… It trained on a dataset taken from Common Crawl, a nonprofit that scrapes text from websites and offers it for free download, Wikipedia, and other web texts, all from 2021.The ChatGPT Plus paid subscription offered web searching capabilities with a …","url":["http://www.ncl.ecu.edu/index.php/NCL/article/view/5420/4989"]}
{"year":"2023","title":"Language Aligned Visual Representations Predict Human Behavior in Naturalistic Learning Tasks","authors":["C Demircan, T Saanum, L Pettini, M Binz… - arXiv preprint arXiv …, 2023"],"snippet":"Humans possess the ability to identify and generalize relevant features of natural objects, which aids them in various situations. To investigate this phenomenon and determine the most effective representations for predicting human behavior, we …","url":["https://arxiv.org/pdf/2306.09377"]}
{"year":"2023","title":"Language and Task Arithmetic with Parameter-Efficient Layers for Zero-Shot Summarization","authors":["A Chronopoulou, J Pfeiffer, J Maynez, X Wang… - arXiv preprint arXiv …, 2023"],"snippet":"… This corpus has been created using a Common Crawl-based dataset covering 101 languages. All languages considered in our experiments are covered by mC4. For the language vectors, we finetune the LLM using LoRA on prefix-LM for only 5k …","url":["https://arxiv.org/pdf/2311.09344"]}
{"year":"2023","title":"Language Is Not All You Need: Aligning Perception with Language Models","authors":["S Huang, L Dong, W Wang, Y Hao, S Singhal, S Ma… - arXiv preprint arXiv …, 2023"],"snippet":"… We also include the Common Crawl snapshots (2020-50 and 2021-04) datasets, CC-Stories… are collected from web pages of the Common Crawl web data by extracting image sources … Interleaved Image-Text Data We collect interleaved …","url":["https://arxiv.org/pdf/2302.14045"]}
{"year":"2023","title":"Language Models and Power Laws","authors":["Ł Dębowski"],"snippet":"… Training data: Common Crawl (410 bln, 60%), WebText2 (19 bln, 22%), books (67 bln, 16%), Wikipedia (3 bln, 3%). …","url":["https://www.researchgate.net/profile/Lukasz-Debowski/publication/368757770_Language_Models_and_Power_Laws/links/63f8a32057495059453e7102/Language-Models-and-Power-Laws.pdf"]}
{"year":"2023","title":"Language Models are Drummers: Drum Composition with Natural Language Pre-Training","authors":["L Zhang, C Callison-Burch - arXiv preprint arXiv:2301.01162, 2023"],"snippet":"Automatic music generation with artificial intelligence typically requires a large amount of data which is hard to obtain for many less common genres and musical instruments. To tackle this issue, we present ongoing work and preliminary findings …","url":["https://arxiv.org/pdf/2301.01162"]}
{"year":"2023","title":"Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training","authors":["M Anschütz, J Oehms, T Wimmer, B Jezierski, G Groh - arXiv preprint arXiv …, 2023"],"snippet":"Automatic text simplification systems help to reduce textual information barriers on the internet. However, for languages other than English, only few parallel data to train these systems exists. We propose a two-step approach to overcome this data …","url":["https://arxiv.org/pdf/2305.12908"]}
{"year":"2023","title":"Language Report French","authors":["G Adda, I Vasilescu, F Yvon - European Language Equality: A Strategic Agenda for …, 2023"],"snippet":"… The CommonCrawl project aggregates Web data that is orders of magnitude larger than these resources; and it is updated on a regular basis. Using French subsets of CommonCrawl, it has been possible to train large language models (LMs) …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-28819-7_16.pdf"]}
{"year":"2023","title":"Language Report Slovenian","authors":["S Krek - European Language Equality: A Strategic Agenda for …, 2023"],"snippet":"Around 2.5 million people around the world speak or understand Slovene, with the vast majority of them living in the Republic of Slovenia where it is the official language. The constitution grants the right to use their mother tongue to Italian and …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-28819-7_34.pdf"]}
{"year":"2023","title":"Language Resources for Dutch Large Language Modelling","authors":["B Vanroy - arXiv preprint arXiv:2312.12852, 2023"],"snippet":"Despite the rapid expansion of types of large language models, there remains a notable gap in models specifically designed for the Dutch language. This gap is not only a shortage in terms of pretrained Dutch models but also in terms of data, and …","url":["https://arxiv.org/pdf/2312.12852"]}
{"year":"2023","title":"Language Variety Identification with True Labels","authors":["M Zampieri, K North, T Jauhiainen, M Felice, N Kumari… - arXiv preprint arXiv …, 2023"],"snippet":"Language identification is an important first step in many IR and NLP applications. Most publicly available language identification datasets, however, are compiled under the assumption that the gold label of each instance is determined by where …","url":["https://arxiv.org/pdf/2303.01490"]}
{"year":"2023","title":"Language-Aware Spatial-Temporal Collaboration for Referring Video Segmentation","authors":["T Hui, S Liu, Z Ding, S Huang, G Li, W Wang, L Liu…"],"snippet":"… The GloVe word embedding [66] pretrained on the Common Crawl with 840B tokens is used to embed input words. The maximum sequence length of the input referring expression is set as 20. The height and width of the input frames are …","url":["http://www.colalab.net/media/paper/CSTM_TPAMI_Paper.pdf"]}
{"year":"2023","title":"Language-Family Adapters for Low-Resource Multilingual Neural Machine Translation","authors":["A Chronopoulou, D Stojanovski, A Fraser - Proceedings of the The Sixth Workshop …, 2023"],"snippet":"Large multilingual models trained with self-supervision achieve state-of-the-art results in a wide range of natural language processing tasks. Self-supervised pretrained models are often fine-tuned on parallel data from one or multiple …","url":["https://aclanthology.org/2023.loresmt-1.5.pdf"]}
{"year":"2023","title":"Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior","authors":["A Khandelwal, A Agrawal, A Bhattacharyya, YK Singla… - arXiv preprint arXiv …, 2023"],"snippet":"… Consider the Common Crawl project1, one common source of data included in most language models; it produces more than 20TB of text … Similarly, while a lot of public blogs and user forums are included in major text corpora used in training …","url":["https://arxiv.org/pdf/2309.00359"]}
{"year":"2023","title":"Large Data-to-Text Generation","authors":["V Sarangian - 2023"],"snippet":"This thesis presents a domain-driven approach to sports game summarization, a specific instance of large data-to-text generation (DTG). We first address the data fidelity issue in the Rotowire dataset by supplementing existing input records and …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19451/Sarangian_Varnan.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"Large Graph Models: A Perspective","authors":["Z Zhang, H Li, Z Zhang, Y Qin, X Wang, W Zhu - arXiv preprint arXiv:2308.14522, 2023"],"snippet":"… This massive amount of data for NLP and CV tasks is typically sourced from publicly accessible human-generated content, such as web pages in CommonCrawl or user-posted photos in social media, which are easily collected from the web. …","url":["https://arxiv.org/pdf/2308.14522"]}
{"year":"2023","title":"Large Language Models (LLM): Need, Methods, And Research Trends","authors":["RM Pir"],"snippet":"… Pre-training and fine-tuning: This technique involves pre-training a large model on a massive dataset, such as Wikipedia or Common Crawl, and then fine-tuning the model on a specific task, such as sentiment analysis or question answering. This …","url":["https://www.ijcspub.org/papers/IJCSP23A1262.pdf"]}
{"year":"2023","title":"Large Language Models and Control Mechanisms Improve Text Readability of Biomedical Abstracts","authors":["Z Li, S Belkadi, N Micheletti, L Han, M Shardlow… - arXiv preprint arXiv …, 2023"],"snippet":"… The authors used the common crawl corpus and filtered to keep only natural text and de-duplication processing. They extracted 750GB of clean English data to feed into the model for multi-task pre-training. Different masking strategies are integrated …","url":["https://arxiv.org/pdf/2309.13202"]}
{"year":"2023","title":"Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset","authors":["S Alavi Naeini, R Saqur, M Saeidi, J Giorgi, B Taati - Advances in Neural Information …, 2024","S Naeini, R Saqur, M Saeidi, J Giorgi, B Taati - arXiv preprint arXiv:2306.11167, 2023"],"snippet":"… We used two FastText models, one pre-trained on the Common Crawl corpus and another on Wikipedia. Approximately 10% of the total clues encountered in the dataset were out-of-vocabulary (OOV). A significant portion (~80%) of the OOV …","url":["https://arxiv.org/pdf/2306.11167","https://proceedings.neurips.cc/paper_files/paper/2023/file/11e3e0f1b29dcd31bd0952bfc1357f68-Paper-Datasets_and_Benchmarks.pdf"]}
{"year":"2023","title":"Large Language Models Can Be Used to Estimate the Ideologies of Politicians in a Zero-Shot Learning Setting","authors":["PY Wu, JA Tucker, J Nagler, S Messing - arXiv preprint arXiv:2303.12057, 2023"],"snippet":"The mass aggregation of knowledge embedded in large language models (LLMs) holds the promise of new solutions to problems of observability and measurement in the social sciences. We examine the utility of one such model for a particularly …","url":["https://arxiv.org/pdf/2303.12057"]}
{"year":"2023","title":"Large Language Models Can Be Used to Estimate the Latent Positions of Politicians","authors":["PY Wu, J Nagler, JA Tucker, S Messing"],"snippet":"Existing approaches to estimating politicians’ latent positions along specific dimensions often fail when relevant data is limited. We leverage the embedded knowledge in generative large language models (LLMs) to address this challenge …","url":["https://www.patrickywu.com/PatrickYWu_JMP1_LaMPscores.pdf"]}
{"year":"2023","title":"Large language models in medicine","authors":["AJ Thirunavukarasu, DSJ Ting, K Elangovan… - Nature Medicine, 2023"],"snippet":"Large language models (LLMs) can respond to free-text queries without being specifically trained in the task in question, causing excitement and concern about their use in healthcare settings. ChatGPT is a generative artificial intelligence (AI) …","url":["https://www.nature.com/articles/s41591-023-02448-8"]}
{"year":"2023","title":"Large Language Models Need Symbolic AI","authors":["K Hammond, D Leake - 2023"],"snippet":"… GPT-3 was trained on an extensive dataset, based on a version of the CommonCrawl dataset (with almost a trillion words) and additional reference sources. Given tasks and few-shot demonstrations provided to the system as text …","url":["https://ceur-ws.org/Vol-3432/paper17.pdf"]}
{"year":"2023","title":"Large Language Models","authors":["M McTear, M Ashurkina - Transforming Conversational AI: Exploring the Power …, 2024","MR Douglas - arXiv preprint arXiv:2307.05782, 2023"],"snippet":"… The model was trained on the Common Crawl, a dataset of billions of words from web pages, and the Bookcorpus dataset, consisting of … The model was trained on a diverse dataset, including Common Crawl and WebText. GPT-2 was able to …","url":["https://arxiv.org/pdf/2307.05782","https://link.springer.com/chapter/10.1007/979-8-8688-0110-5_4"]}
{"year":"2023","title":"Large Language Models' Understanding of Math: Source Criticism and Extrapolation","authors":["R Yousefzadeh, X Cao - arXiv preprint arXiv:2311.07618, 2023"],"snippet":"… Common Crawl is particularly interesting. The GPT-f model developed for mathematical learning was trained on 300 billion tokens from CommonCrawl… The size of the most recent CommonCrawl is 390 TiB including the contents of 3.1 billion …","url":["https://arxiv.org/pdf/2311.07618"]}
{"year":"2023","title":"Large Language Models, scientific knowledge and factuality: A systematic analysis in antibiotic discovery","authors":["M Wysocka, O Wysocki, M Delmas, V Mutel, A Freitas - arXiv preprint arXiv …, 2023"],"snippet":"Inferring over and extracting information from Large Language Models (LLMs) trained on a large corpus of scientific literature can potentially drive a new era in biomedical research, reducing the barriers for accessing existing medical evidence …","url":["https://arxiv.org/pdf/2305.17819"]}
{"year":"2023","title":"Large Scale Fine-Tuned Transformers Models Application for Business Names Generation","authors":["M Lukauskas, T Rasymas, M Minelga, D Vaitmonas - Computing and Informatics, 2023"],"snippet":"… on larger datasets, leading to pre-trained systems such as BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer), which have been trained on large language datasets such as the …","url":["https://www.cai.sk/ojs/index.php/cai/article/download/2023_3_525/1228"]}
{"year":"2023","title":"Large Sentiment Dictionary of Russian Words","authors":["VV Bochkarev, AA Achkeev, AV Savinkov… - … International Conference on …, 2023"],"snippet":"… Vector sets for 157 languages, trained on the Common Crawl corpus using the most advanced word embedding algorithms at the time, were made publicly available in 2018. The great advantage of this dataset in terms of the tasks set in our …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47640-2_6"]}
{"year":"2023","title":"Large Web Archive Collection Infrastructure and Services","authors":["X Wang - 2023"],"snippet":"… We use Common Crawl’s web archiving data crawled from May 20 to 23, 2018. The data set consists of 1219 Gzip compressed WARC files totaling 0.98 TB, and contains 53,324,440 records. The WARC files are organized by crawling time, each …","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/113345/Wang_X_D_2023.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"Large-scale Security Analysis of HTTP Responses","authors":["J Carbol, H Stegrell - 2023"],"snippet":"… In order to find vulnerabilities on a large scale, this thesis utilizes the crawl data from Common Crawl, an open repository of web crawl data. In this data, indicators of specific programs, software, or libraries are visible, allowing us to find vulnerable …","url":["http://odr.chalmers.se/bitstreams/8f327562-4385-4640-a3eb-ae07818230a5/download"]}
{"year":"2023","title":"LASTING IMPACT: WHY YOU SHOULD CARE ABOUT COURT OF CUSTOMS AND PATENT APPEAL CASES","authors":["J Glendenning - 2023"],"snippet":"… sentence and understand that machine learning models like GPT-3 don't \"read\" like humans do, but rather ingest data sets like Common Crawl, which is made up of many written works … 2020) (explaining the use of the Common Crawl dataset in …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/aiplaqj51&section=3"]}
{"year":"2023","title":"Lawyer LLaMA Technical Report","authors":["Q Huang, M Tao, Z An, C Zhang, C Jiang, Z Chen… - arXiv preprint arXiv …, 2023"],"snippet":"… On one hand, current LLMs are primarily trained on general corpora such as Common Crawl and Wikipedia, with limited exposure to domainspecific resources. Therefore, they lack the necessary knowledge required for specific domains. On the …","url":["https://arxiv.org/pdf/2305.15062"]}
{"year":"2023","title":"LCTs at HODI: Homotransphobic Speech Detection on Italian Tweets","authors":["D Locatelli, L Locatelli - Proceedings of the Eighth Evaluation Campaign of …, 2023"],"snippet":"… -Commoncrawl-Cased version. Using the HuggingFace Transformers library [11], we applied a classification head on top of the model outputs, which enabled us to fine-tune the base model on the HODI data for Subtask A. The selection of the …","url":["https://ceur-ws.org/Vol-3473/paper30.pdf"]}
{"year":"2023","title":"Learning Human-Human Interactions in Images from Weak Textual Supervision","authors":["M Alper, H Averbuch-Elor - arXiv preprint arXiv:2304.14104, 2023"],"snippet":"Interactions between humans are diverse and context-dependent, but previous works have treated them as categorical, disregarding the heavy tail of possible interactions. We propose a new paradigm of learning human-human interactions as …","url":["https://arxiv.org/pdf/2304.14104"]}
{"year":"2023","title":"Learning Language-Specific Layers for Multilingual Machine Translation","authors":["TP Pires, RM Schmidt, YH Liao, S Peitz - arXiv preprint arXiv:2305.02665, 2023"],"snippet":"Multilingual Machine Translation promises to improve translation quality between non-English languages. This is advantageous for several reasons, namely lower latency (no need to translate twice), and reduced error cascades (eg, avoiding …","url":["https://arxiv.org/pdf/2305.02665"]}
{"year":"2023","title":"Learning word embeddings for Ukrainian: A comparative study of fastText hyperparameters","authors":["N Romanyshyn, D Chaplynskyi, K Zakharov - Proceedings of the Second Ukrainian …, 2023"],"snippet":"… noisy data from the Common Crawl (CC) project4 for learning their word vectors. Another shortcoming is that they did not optimize subword … It was a deliberate decision not to include Common Crawl or Oscar13 corpora data into UberText because …","url":["https://aclanthology.org/2023.unlp-1.3.pdf"]}
{"year":"2023","title":"Legal Governance of Internet Information Content in AIGC Era Taking Large Language Model as an Example","authors":["LI Mingxuan, WEN Jirong - Journal of Beijing Institute of Technology (Social …, 2023"],"snippet":"… 以 GPT-3,PaLM 和 LLaMa 这三个具有代表性的大语言模型为例,GPT-3 的预训练 数据包含 Common Crawl,WebText 2 和维基百科,PaLM 的预训练数据包含社交媒体 对话,过滤后的网页,Github, 多语言维基百科和新闻,LLaMa 的预训练数据包含 Common …","url":["http://journal.bit.edu.cn/sk/en/article/pdf/preview/10.15918/j.jbitss1009-3370.2023.1592.pdf"]}
{"year":"2023","title":"Lemur: Harmonizing Natural Language and Code for Language Agents","authors":["Y Xu, H Su, C Xing, B Mi, Q Liu, W Shi, B Hui, F Zhou… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce Lemur and Lemur-Chat, openly accessible language models optimized for both natural language and coding capabilities to serve as the backbone of versatile language agents. The evolution from language chat models to …","url":["https://arxiv.org/pdf/2310.06830"]}
{"year":"2023","title":"Let's Chat to Find the APIs: Connecting Human, LLM and Knowledge Graph through AI Chain","authors":["Q Huang, Z Wan, Z Xing, C Wang, J Chen, X Xu, Q Lu - arXiv preprint arXiv …, 2023"],"snippet":"… an analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2309.16134"]}
{"year":"2023","title":"Let's Discover More API Relations: A Large Language Model-based AI Chain for Unsupervised API Relation Inference","authors":["Q Huang, Y Sun, Z Xing, Y Cao, J Chen, X Xu, H Jin… - arXiv preprint arXiv …, 2023"],"snippet":"… are pre-trained on the corpus of the entire Internet (Common Crawl [11]), which are referred to as foundation models [12]. As such foundation LLMs pack the knowledge of the entire Web, we are no longer limited to the scope of API text corpus …","url":["https://arxiv.org/pdf/2311.01266"]}
{"year":"2023","title":"Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource Translation","authors":["S Nayak, S Ranathunga, S Thillainathan, R Hung… - arXiv preprint arXiv …, 2023"],"snippet":"NMT systems trained on Pre-trained Multilingual Sequence-Sequence (PMSS) models flounder when sufficient amounts of parallel data is not available for fine-tuning. This specifically holds for languages missing/under-represented in these models …","url":["https://arxiv.org/pdf/2306.01382"]}
{"year":"2023","title":"Leveraging Closed-Access Multilingual Embedding for Automatic Sentence Alignment in Low Resource Languages","authors":["I Abdulmumin, AA Khalid, SH Muhammad, IS Ahmad… - arXiv preprint arXiv …, 2023"],"snippet":"… Using a similarity metric in that multimodal embedding space, they performed mining of audio in German, French, Spanish, and English from Librivox against billions of sentences from Common Crawl. This yielded more than twenty thousand …","url":["https://arxiv.org/pdf/2311.12179"]}
{"year":"2023","title":"Leveraging Diffusion Perturbations for Measuring Fairness in Computer Vision","authors":["N Lui, B Chia, W Berrios, C Ross, D Kiela - arXiv preprint arXiv:2311.15108, 2023"],"snippet":"Computer vision models have been known to encode harmful biases, leading to the potentially unfair treatment of historically marginalized groups, such as people of color. However, there remains a lack of datasets balanced along demographic traits …","url":["https://arxiv.org/pdf/2311.15108"]}
{"year":"2023","title":"Leveraging Domain Adaptation and Data Augmentation to Improve Qur'anic IR in English and Arabic","authors":["V Pavlova - arXiv preprint arXiv:2312.02803, 2023"],"snippet":"In this work, we approach the problem of Qur'anic information retrieval (IR) in Arabic and English. Using the latest state-of-the-art methods in neural IR, we research what helps to tackle this task more efficiently. Training retrieval models requires a lot of …","url":["https://arxiv.org/pdf/2312.02803"]}
{"year":"2023","title":"Leveraging Feature Selection to Improve the Accuracy for Malware Detection","authors":["D Smith, S Khorsandroo, K Roy - 2023"],"snippet":"Malware is becoming increasingly sophisticated and difficult to detect with traditional monitoring tools and antivirus software. As a result, machine learning has become a popular approach for classifying and detecting malware-related data. In this study …","url":["https://www.researchsquare.com/article/rs-3045391/latest.pdf"]}
{"year":"2023","title":"Leveraging Function Space Aggregation for Federated Learning at Scale","authors":["N Dhawan, N Mitchell, Z Charles, Z Garrett… - arXiv preprint arXiv …, 2023"],"snippet":"… C4 and CC-News are hosted by commoncrawl.org and we access both through HuggingFace datasets. … C4 The Colossal Clean Crawled Corpus (C4) dataset is a cleaned version of Common Crawl’s web crawl corpus (Raffel et al., 2020). We use …","url":["https://arxiv.org/pdf/2311.10291"]}
{"year":"2023","title":"Leveraging Image-Text Similarity and Caption Modification for the DataComp Challenge: Filtering Track and BYOD Track","authors":["S Yokoo, P Zhu, Y Ishikawa, M Tanaka, M Kondo… - arXiv preprint arXiv …, 2023"],"snippet":"… DataComp provides a new candidate pool of 12.8B image-text pairs collected from Common Crawl. This challenge contains four distinct compute and data scales. In this work, we mainly focus on the small scale (12.8M samples). …","url":["https://arxiv.org/pdf/2310.14581"]}
{"year":"2023","title":"Leveraging Prior Knowledge and Structure for Data-Efficient Machine Learning","authors":["B Gunel - 2022"],"snippet":"Building high-performing end-to-end machine learning systems primarily consists of developing the machine learning model and gathering high-quality training data for the application of interest, assuming one has access to the right hardware. Although …","url":["https://search.proquest.com/openview/02abeb62b4586808841b511d8c6b8891/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions","authors":["N San, M Bartelds, B Billings, E de Falco, H Feriza… - arXiv preprint arXiv …, 2023"],"snippet":"Recent research using pre-trained transformer models suggests that just 10 minutes of transcribed speech may be enough to fine-tune such a model for automatic speech recognition (ASR) -- at least if we can also leverage vast amounts of text …","url":["https://arxiv.org/pdf/2302.04975"]}
{"year":"2023","title":"LFWE: L inguistic F eature Based W ord E mbedding for Hindi Fake News Detection","authors":["R Sharma, A Arya - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"It is essential for the research communities to investigate ways for authenticating news. The use of linguistic feature-based analysis to automatically detect false news is gaining popularity among the scientific community. However, such techniques are …","url":["https://dl.acm.org/doi/pdf/10.1145/3589764"]}
{"year":"2023","title":"LibriSpeech-PC: Benchmark for Evaluation of Punctuation and Capitalization Capabilities of end-to-end ASR Models","authors":["A Meister, M Novikov, N Karpov, E Bakhturina… - arXiv preprint arXiv …, 2023"],"snippet":"… To enrich our LM model with more diverse examples of punctuation and capitalization, we download a random subset from the Common Crawl dataset [20]. The Common Crawl subset is 100 times bigger than LibriSpeech-PC and is normalized …","url":["https://arxiv.org/pdf/2310.02943"]}
{"year":"2023","title":"Life-long phishing attack detection using continual learning","authors":["A Ejaz, AN Mian, S Manzoor - Scientific Reports, 2023"],"snippet":"… Also, FastText is trained on a common crawl dataset consisting of web pages related to our problem. Word2Vec and Glove are small and used for non-complex tasks, while ELMo and BERT are very complex models used for complex tasks. …","url":["https://www.nature.com/articles/s41598-023-37552-9"]}
{"year":"2023","title":"Lightweb: Private web browsing without all the baggage","authors":["E Dauterman, H Corrigan-Gibbs - 2023"],"snippet":"This paper proposes lightweb, a new system for private browsing. A lightweb client can browse a web of textbased pages without revealing to anyone—not the network, not the servers hosting the pages—which pages it is reading. Unlike Tor and other …","url":["https://people.csail.mit.edu/henrycg/files/academic/papers/lightweb.pdf"]}
{"year":"2023","title":"Limitations of democratic rights during the Covid-19 pandemic—exploring the citizens' perception and discussions on dangers to democracy in Germany","authors":["A Katsanidou, M Kneuer, F Bensmann, D Dimitrov… - Zeitschrift für Vergleichende …, 2023"],"snippet":"The governments’ mitigation measures to fight the COVID-19 pandemic are unprecedented in our post-war history. For overcoming this crisis, citizens were expected to act in compliance with these measures in order to control the spread of …","url":["https://link.springer.com/article/10.1007/s12286-023-00556-w"]}
{"year":"2023","title":"Linear Mappings: Semantic Transfer from Transformer Models for Cognate Detection and Coreference Resolution","authors":["A Nath - 2022"],"snippet":"Embeddings or vector representations of language and their properties are useful for under-standing how Natural Language Processing technology works. The usefulness of embeddings, however, depends on how contextualized or information-rich …","url":["https://mountainscholar.org/bitstream/handle/10217/235958/Nath_colostate_0053N_17510.pdf?sequence=1"]}
{"year":"2023","title":"Lingualyzer: A computational linguistic tool for multilingual and multidimensional text analysis","authors":["GM Linders, MM Louwerse - Behavior Research Methods, 2023"],"snippet":"… resources utilize large amounts of publicly available data in many languages, such as data coming from Wikipedia and Common Crawl. … We used the 300 dimensional fastText word vectors, which were created from Wikipedia and Common …","url":["https://link.springer.com/article/10.3758/s13428-023-02284-1"]}
{"year":"2023","title":"Linking Representations with Multimodal Contrastive Learning","authors":["A Arora, X Yang, SY Jheng, M Dell - arXiv preprint arXiv:2304.03464, 2023"],"snippet":"… [52] find that GPT-3 performs substantially better on samples from ReCoRD that have near duplicates in RealNews, a subset of Common Crawl included in the GPT-3 training data, compared to those that did not. While most deduplication of noisy text …","url":["https://arxiv.org/pdf/2304.03464"]}
{"year":"2023","title":"Literature Review: Challenges In Creating A Generic Model For Text Classification In Multiple Languages","authors":["R Sinha, R Srivastava - resmilitaris, 2023"],"snippet":"… Authors [60] used a dataset that included Wikipedia and Common Crawl to train the Skip-gram and CBOW word vector models. They also developed a quick language identifier that recognizes 176 different languages. While researchers [61]evaluated …","url":["https://resmilitaris.net/menu-script/index.php/resmilitaris/article/download/2911/2364"]}
{"year":"2023","title":"LLaMA 2: The New Open Source Language Model","authors":["N Jayaseelan"],"snippet":"Language models have revolutionized the field of artificial intelligence, by enabling machines to understand and generate human-like text. Among the plethora of language models, LLaMA (Large Language Models AI) stands out as the latest …","url":["https://www.e2enetworks.com/blog/llama-2-the-new-open-source-language-model"]}
{"year":"2023","title":"LLaMA: Open and Efficient Foundation Language Models","authors":["H Touvron, T Lavril, G Izacard, X Martinet, MA Lachaux… - arXiv preprint arXiv …, 2023"],"snippet":"… We preprocess five CommonCrawl dumps, ranging from 2017 to 2020, with the CCNet pipeline (… We expect these biases to come from CommonCrawl despite multiple filtering steps. … This allowed to train a 5-gram model on 975 billions tokens …","url":["https://arxiv.org/pdf/2302.13971"]}
{"year":"2023","title":"LLEMMA: AN OPEN LANGUAGE MODEL FOR MATHEMATICS","authors":["Z Azerbayev, H Schoelkopf, K Paster, M Dos Santos… - Minerva"],"snippet":"We present LLEMMA, a large language model for mathematics. We continue pretraining Code Llama on Proof-Pile-2, a mixture of scientific papers, web data containing mathematics, and mathematical code, yielding LLEMMA. On the MATH …","url":["https://arxiv.org/pdf/2310.10631"]}
{"year":"2023","title":"LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked","authors":["A Helbling, M Phute, M Hull, DH Chau - arXiv preprint arXiv:2308.07308, 2023"],"snippet":"Large language models (LLMs) have skyrocketed in popularity in recent years due to their ability to generate high-quality text in response to human prompting. However, these models have been shown to have the potential to generate harmful content in …","url":["https://arxiv.org/pdf/2308.07308"]}
{"year":"2023","title":"LLM's for Spanish Song Text Analysis and Classification Using Language Variants","authors":["O García-Vázquez, T Alcántara, H Calvo, G Sidorov - … International Conference on …, 2023"],"snippet":"… The results show that tweets are the best for song lyrics analysis, while Google News and Common Crawl are the best for movie analysis, since the vocabulary that used in these portals is very similar in both cases. Models trained with GLoVe …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47640-2_10"]}
{"year":"2023","title":"LLM-augmented Preference Learning from Natural Language","authors":["I Kang, S Ruan, T Ho, JC Lin, F Mohsin, O Seneviratne… - arXiv preprint arXiv …, 2023"],"snippet":"… The authors query for sentences that contain mentions of both alternatives from the Common Crawl dataset and present a final dataset of 7,199 sentences with 217 unique pairs of alternatives and 3 classes – 𝐴 ≻ 𝐵, 𝐴 ≺ 𝐵, N/A. Because of the …","url":["https://arxiv.org/pdf/2310.08523"]}
{"year":"2023","title":"LLM-QAT: Data-Free Quantization Aware Training for Large Language Models","authors":["Z Liu, B Oguz, C Zhao, E Chang, P Stock, Y Mehdad… - arXiv preprint arXiv …, 2023"],"snippet":"Several post-training quantization methods have been applied to large language models (LLMs), and have been shown to perform well down to 8-bits. We find that these methods break down at lower bit precision, and investigate quantization …","url":["https://arxiv.org/pdf/2305.17888"]}
{"year":"2023","title":"LLM-RM at SemEval-2023 Task 2: Multilingual Complex NER using XLM-RoBERTa","authors":["R Mehta, V Varma - arXiv preprint arXiv:2305.03300, 2023"],"snippet":"Named Entity Recognition(NER) is a task of recognizing entities at a token level in a sentence. This paper focuses on solving NER tasks in a multilingual setting for complex named entities. Our team, LLM-RM participated in the recently organized …","url":["https://arxiv.org/pdf/2305.03300"]}
{"year":"2023","title":"LLM360: Towards Fully Transparent Open-Source LLMs","authors":["Z Liu, A Qiao, W Neiswanger, H Wang, B Tan, T Tao… - arXiv preprint arXiv …, 2023"],"snippet":"The recent surge in open-source Large Language Models (LLMs), such as LLaMA, Falcon, and Mistral, provides diverse options for AI practitioners and researchers. However, most LLMs have only released partial artifacts, such as the final model …","url":["https://arxiv.org/pdf/2312.06550"]}
{"year":"2023","title":"LLMs: A Promising New Tool for Improving Healthcare in Low-Resource Nations","authors":["A Gangavarapu - 2023 IEEE Global Humanitarian Technology …, 2023"],"snippet":"This paper explores the potential of large language models (LLMs) in addressing healthcare inequalities, particularly in underserved nations with provider shortages, limited resources, and funding constraints. The UN’s Sustainable Development Goal …","url":["https://ieeexplore.ieee.org/abstract/document/10354650/"]}
{"year":"2023","title":"LMU at HaSpeeDe3: Multi-Dataset Training for Cross-Domain Hate Speech Detection","authors":["V Hangya, A Fraser - 2023"],"snippet":"We describe LMU Munich’s hate speech detection system for participating in the cross-domain track of the HaSpeeDe3 shared task at EVALITA 2023. The task focuses on the politics and religion domains, having no in-domain training data for …","url":["https://ceur-ws.org/Vol-3473/paper24.pdf"]}
{"year":"2023","title":"Logical definition-based identification of potential missing concepts in SNOMED CT","authors":["X Hao, R Abeysinghe, K Roberts, L Cui - BMC Medical Informatics and Decision …, 2023"],"snippet":"Biomedical ontologies are representations of biomedical knowledge that provide terms with precisely defined meanings. They play a vital role in facilitating biomedical research in a cross-disciplinary manner. Quality issues of biomedical …","url":["https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-023-02183-7"]}
{"year":"2023","title":"Long Form Question Answering Dataset Creation for Business Use Cases using Noise-Added Siamese-BERT","authors":["T Cekiç, Y Manav, B Helvacıoglu, EB Dündar, O Deniz… - 2022"],"snippet":"… To generate related documents, they use a TFIDF retriever on the CommonCrawl web dump, to retrieve related documents and combine all documents related parts to generate one supporting document.In the KILT (Petroni et al., 2021) benchmark …","url":["https://www.scitepress.org/Papers/2022/115509/115509.pdf"]}
{"year":"2023","title":"LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery","authors":["T Chen, T Ding, B Yadav, I Zharkov, L Liang"],"snippet":"Large Language Models (LLMs) have transformed the landscape of artificial intelligence, while their enormous size presents significant challenges in terms of computational costs. We introduce LoRAShear, a novel efficient approach to …","url":["https://www.researchgate.net/profile/Tianyi-Chen-36/publication/374945275_LoRAShear_Efficient_Large_Language_Model_Structured_Pruning_and_Knowledge_Recovery/links/65382b2873a2865c7ad0f1a4/LoRAShear-Efficient-Large-Language-Model-Structured-Pruning-and-Knowledge-Recovery.pdf"]}
{"year":"2023","title":"Lost in Translation: Large Language Models in Non-English Content Analysis","authors":["G Nicholas, A Bhatia - arXiv preprint arXiv:2306.07377, 2023"],"snippet":"In recent years, large language models (eg, Open AI's GPT-4, Meta's LLaMa, Google's PaLM) have become the dominant approach for building AI systems to analyze and generate language online. However, the automated systems that …","url":["https://arxiv.org/pdf/2306.07377"]}
{"year":"2023","title":"Low Resource Summarization using Pre-trained Language Models","authors":["M Munaf, H Afzal, N Iltaf, K Mahmood - arXiv preprint arXiv:2310.02790, 2023"],"snippet":"With the advent of Deep Learning based Artificial Neural Networks models, Natural Language Processing (NLP) has witnessed significant improvements in textual data processing in terms of its efficiency and accuracy. However, the research is mostly …","url":["https://arxiv.org/pdf/2310.02790"]}
{"year":"2023","title":"Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgin","authors":["PJ Lin, M Saeed, E Chang, M Scholman - arXiv preprint arXiv:2307.00382, 2023"],"snippet":"Developing effective spoken language processing systems for low-resource languages poses several challenges due to the lack of parallel data and limited resources for fine-tuning models. In this work, we target on improving upon both text …","url":["https://arxiv.org/pdf/2307.00382"]}
{"year":"2023","title":"Low-resource image captioning","authors":["M Du Plessis - 2022"],"snippet":"… The language model is pretrained on the colossal clean crawled corpus (C4), which is a cleaned version of the common crawl dataset [70] and consists of 700 GB of unlabelled text. The cleaning applications include removing non-English text …","url":["https://scholar.sun.ac.za/bitstream/handle/10019.1/126059/duplessis_low_2022.pdf?sequence=1"]}
{"year":"2023","title":"LSTM-Based Encoder–Decoder Attention Model for Text Translation and Simplification on the Constitution of India","authors":["M Navlakha, R Lobo, R Bhargava, RB Karani - … in Computing: ICRIC 2022, Volume 2, 2023"],"snippet":"Natural language processing techniques can be used on judicial and legislative documents like the Constitution for making it more accessible to the general audience. Various approaches such as Natural Machine Translation (NMT), text …","url":["https://link.springer.com/chapter/10.1007/978-981-99-0601-7_64"]}
{"year":"2023","title":"LT at SemEval-2023 Task 1: Effective Zero-Shot Visual Word Sense Disambiguation Approaches using External Knowledge Sources","authors":["F Schneider, C Biemann"],"snippet":"… Further, we assessed the suitability of three external knowledge sources: Wikipedia, a large-scale English Common Crawl corpus, and the multi-modal knowledge graph VisualSem. Our best-performing approach involved the Common …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2023-schneider-et-al-semeval-task-1-vwsd.pdf"]}
{"year":"2023","title":"M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models","authors":["W Zhang, SM Aljunied, C Gao, YK Chia, L Bing - arXiv preprint arXiv:2306.05179, 2023"],"snippet":"… We rank languages by their ratio in the CommonCrawl corpus, which is a widely-used data source for training LLMs. It can be observed that our selected languages span a wide range, from high-resource languages like English and Chinese, to extremely …","url":["https://arxiv.org/pdf/2306.05179"]}
{"year":"2023","title":"MA-INF 4328","authors":["DRE DEMIDOVA"],"snippet":"… • GeoVectors adopts the 300-dimensional English word vectors trained on the Common Crawl, and Wikipedia …","url":["https://www.lostinthe.cloud/Spatial/STDA12-Geographic%20Entity%20Linking.pdf"]}
{"year":"2023","title":"MACEDONIZER-The Macedonian Transformer Language Model","authors":["J Dobreva, T Pavlov, K Mishev, M Simjanoska… - International Conference on …, 2022"],"snippet":"Contextualized language models are becoming omnipresent in the field of Natural Language Processing (NLP). Their learning representation capabilities show dominant results in almost all downstream NLP tasks. The main challenge that low-resource …","url":["https://link.springer.com/chapter/10.1007/978-3-031-22792-9_5"]}
{"year":"2023","title":"Machine learning and Bayesian inference in nuclear fusion research: an overview","authors":["A Pavone, A Merlo, S Kwak, J Svensson - Plasma Physics and Controlled Fusion, 2023"],"snippet":"This article reviews applications of Bayesian inference and machine learning in nuclear fusion research. Current and next-generation nuclear fusion experiments require analysis and modelling efforts that integrate different models consistently …","url":["https://iopscience.iop.org/article/10.1088/1361-6587/acc60f/pdf"]}
{"year":"2023","title":"Machine Learning and Collective Unintelligence","authors":["E Fournier-Tombs - Gender Reboot: Reprogramming Gender Rights in the …, 2023"],"snippet":"… The Common Crawl data, which is a sizable collection of articles pulled from the Internet (as its name suggests), is well known for having significant gender bias. WebText is a very comparable data source that was also created by OpenAI by web …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41390-2_9"]}
{"year":"2023","title":"Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023 …","authors":["D Koutra, C Plant, MG Rodriguez, E Baralis, F Bonchi - 2023"],"snippet":"The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023 …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RYDXEAAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=OkkriZylPk&sig=cgEvn9s2ibUQ-Y4Bnh_3e_AbxWU"]}
{"year":"2023","title":"Machine Learning for Malicious URL Classification: A Temporal Analysis","authors":["EN Wehr - 2024"],"snippet":"When Machine Learning (ML) is applied to labelled datasets, it is standard practice that 70% of the dataset is used for training models, with 30% used for testing. That approach assumes the dataset does not change over time. This praxis makes the …","url":["https://search.proquest.com/openview/046bd0f2e3b912dcc732f0f7e3e4772f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"MACHINE LEARNING IN CYBERSECURITY: COMPREHENSIVE ANALYSIS AND DETECTION OF URL PHISHING ATTACKS","authors":["B Patel - Journal of Research Administration, 2023"],"snippet":"In the face of escalating cyber threats, particularly phishing attacks, this research provides a comprehensive analysis of machine learning techniques for effective phishing URL detection. Leveraging a meticulously curated dataset comprising …","url":["https://journalra.org/index.php/jra/article/download/417/226"]}
{"year":"2023","title":"Machine Learning Insights into Multifaceted Social Impacts on Global Urban Slum Population","authors":["S Shan - 2023"],"snippet":"The growth of the urban slum population proportion highlights the extent of urban inequality. This article uses machine learning to surpass the limitations of traditional static linear regression models. By handling large data volumes and uncovering …","url":["https://www.researchsquare.com/article/rs-3137402/latest.pdf"]}
{"year":"2023","title":"Machine Learning Model for Paraphrases Detection Based on Text Content Pair Binary Classification","authors":["N Kholodna, V Vysotska, O Markiv, S Chyrun"],"snippet":"This article dwells process of ML-model development for detecting paraphrasing by binary classification of texts pair. For this study, the following semantic similarity metrics or indicators have been selected as features: Jacquard coefficient for shared …","url":["https://ceur-ws.org/Vol-3312/paper23.pdf"]}
{"year":"2023","title":"Machine Learning on Knowledge Graphs for Health applications.","authors":["D Scala"],"snippet":"In the past decade, many impressive results have been reported for machine learning (ML) tools that are developed to assist in clinical decision making. However, translating these largely theoretical achievements to realistic settings remains a …","url":["https://picuslab.dieti.unina.it/images/pdfs/_TESI__DOROTEA_SCALA.pdf"]}
{"year":"2023","title":"Machine Learning-Based Phishing Detection Using URL Features: A Comprehensive Review","authors":["AUZ Asif, H Shirazi, I Ray - International Symposium on Stabilizing, Safety, and …, 2023"],"snippet":"… Common Crawl is a large-scale web crawl that is made up of petabytes of data that have been collected since 2008. It includes raw web page data, extracted metadata, and text extractions. This repository’s material is maintained in Web …","url":["https://link.springer.com/chapter/10.1007/978-3-031-44274-2_36"]}
{"year":"2023","title":"Machine translation and its evaluation: a study","authors":["SK Mondal, H Zhang, HMD Kabir, K Ni, HN Dai - Artificial Intelligence Review, 2023"],"snippet":"Abstract Machine translation (namely MT) has been one of the most popular fields in computational linguistics and Artificial Intelligence (AI). As one of the most promising approaches, MT can potentially break the language barrier of people from all over …","url":["https://link.springer.com/article/10.1007/s10462-023-10423-5"]}
{"year":"2023","title":"Machine visions: Mapping depictions of machine vision through critical image synthesis","authors":["R Carter, RA Carter - Open Library of Humanities, 2023"],"snippet":"This paper conducts a speculative examination of how AI image synthesisers, which generate novel imagery in response to inputted textual prompts – such as DALL-E, Midjourney, and Stable Diffusion – can be employed reflexively to investigate …","url":["https://olh.openlibhums.org/articles/10.16995/olh.10077/"]}
{"year":"2023","title":"Machine-Assisted Social Psychology Hypothesis Generation","authors":["S Banker, P Chatterjee, H Mishra, A Mishra - 2023"],"snippet":"… GPT-3 was developed by OpenAI and has been trained on several large text corpora such as Common Crawl, Wikipedia, digitized books, WebText2 (which is based on Reddit posts), etc., amounting to about 45 terabytes of training data. GPT-3 …","url":["https://psyarxiv.com/kv6f7/download?format=pdf"]}
{"year":"2023","title":"MADLAD-400: A Multilingual And Document-Level Large Audited Dataset","authors":["S Kudugunta, I Caswell, B Zhang, X Garcia… - arXiv preprint arXiv …, 2023"],"snippet":"… We introduce MADLAD-400, a manually audited, general domain 3T token monolingual dataset based on CommonCrawl, spanning 419 languages. We discuss the limitations revealed by self-auditing MADLAD-400, and the role data auditing had in …","url":["https://arxiv.org/pdf/2309.04662"]}
{"year":"2023","title":"MahaEmoSen: Towards Emotion-aware Multimodal Marathi Sentiment Analysis","authors":["P Chaudhari, P Nandeshwar, S Bansal, N Kumar - ACM Transactions on Asian and …, 2023"],"snippet":"… It is a BERT-based model trained on PMINDIA [13], commoncrawl [14], Wikipedia3, Dakshina corpus [15] for 17 diferent Indic languages like Hindi, Marathi, Tamil etc. It is also trained on … Total of 100 languages from CommonCrawl data were used as …","url":["https://dl.acm.org/doi/pdf/10.1145/3618057"]}
{"year":"2023","title":"Make PDF safe again","authors":["K DORNER"],"snippet":"Malware is an ever-present problem, and while most people are aware that executable files can be dangerous, other file formats are deemed as trustworthy and safe. One of these file formats is PDF. Billions of PDF files are created each day and …","url":["https://phaidra.fhstp.ac.at/detail/o:5121.pdf"]}
{"year":"2023","title":"Making Changes in Webpages Discoverable: A Change-Text Search Interface for Web Archives","authors":["L Frew, ML Nelson, MC Weigle - arXiv preprint arXiv:2305.00546, 2023"],"snippet":"Webpages change over time, and web archives hold copies of historical versions of webpages. Users of web archives, such as journalists, want to find and view changes on webpages over time. However, the current search interfaces for web …","url":["https://arxiv.org/pdf/2305.00546"]}
{"year":"2023","title":"Man vs the machine: The Struggle for Effective Text Anonymisation in the Age of Large Language Models","authors":["C Patsakis, N Lykousas - arXiv preprint arXiv:2303.12429, 2023"],"snippet":"… According to OpenAI, the training data for GPT-3 includes various sources such as books, articles, and websites, with a primary source being the Common Crawl2, a repository of web pages and documents that is regularly updated and maintained …","url":["https://arxiv.org/pdf/2303.12429"]}
{"year":"2023","title":"Man vs. Machine: An applied study comparing a man-made lexicon, a machine learned lexicon, and OpenAI's GPT for sentiment analysis.","authors":["MA Alexandersen, J Rutlin - 2023"],"snippet":"Sentiment analysis, at scale, has become an essential tool in the methodological toolbox of finance. In this thesis, we construct a sentiment lexicon using a supervised machine learning model by Taddy (2013) and compare it to the traditional finance …","url":["https://openaccess.nhh.no/nhh-xmlui/bitstream/handle/11250/3088766/masterthesis.pdf?sequence=1"]}
{"year":"2023","title":"Mapping Language Literacy At Scale: A Case Study on Facebook","authors":["YR Lin, S Wu, W Mason - arXiv preprint arXiv:2303.12179, 2023"],"snippet":"Literacy is one of the most fundamental skills for people to access and navigate today's digital environment. This work systematically studies the language literacy skills of online populations for more than 160 countries and regions across the world …","url":["https://arxiv.org/pdf/2303.12179"]}
{"year":"2023","title":"MARGEN: Marathi Question Answering Generative Conversation Model","authors":["SV Bhalshankar, RR Deshmukh - … Conference on Applications of Machine Intelligence …, 2023"],"snippet":"The conversational system aka chatbot market capture was worth USD 526 million in 2021 around the world. The innovations created such as Machine learning, Deep learning, Natural Language Processing (NLP), and Big data analytics have given a …","url":["https://www.atlantis-press.com/article/125986308.pdf"]}
{"year":"2023","title":"Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Search","authors":["C Jenkins, S Agarwal, J Barry, S Fincke, E Boschee - arXiv preprint arXiv:2305.10561, 2023"],"snippet":"In this paper, we present ISI-Clear, a state-of-the-art, cross-lingual, zero-shot event extraction system and accompanying user interface for event visualization & search. Using only English training data, ISI-Clear makes global events available on-demand …","url":["https://arxiv.org/pdf/2305.10561"]}
{"year":"2023","title":"MatSciRE: Leveraging pointer networks to automate entity and relation extraction for material science knowledge-base construction","authors":["A Mullick, A Ghosh, GS Chaitanya, S Ghui, T Nayak… - Computational Materials …, 2024"],"snippet":"Material science literature is a rich source of factual information about various categories of entities (like materials and compositions) and various relations between these entities, such as conductivity, voltage, etc. Automatically extracting …","url":["https://www.sciencedirect.com/science/article/pii/S0927025623006535"]}
{"year":"2023","title":"Mazen ALSAREM","authors":["SS via Query-Biased"],"snippet":"In our knowledge-driven society, the acquisition and the transfer of knowledge play a principal role. Web search engines are somehow tools for knowledge acquisition and transfer from the web to the user. The search engine results page (SERP) …","url":["https://hal.science/tel-01327769v1/preview/Thesis.pdf"]}
{"year":"2023","title":"MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods","authors":["M Finkelstein, M Freitag - arXiv preprint arXiv:2309.10966, 2023"],"snippet":"… For that, we take a random sample of 200,000 English sentences from Common Crawl1. … Phase 2 MBR and QE finetuning from the base checkpoint on the larger Common Crawl … on either self-QE-Common-Crawl or self-MBRCommon-Crawl …","url":["https://arxiv.org/pdf/2309.10966"]}
{"year":"2023","title":"MCPG: A Flexible Multi-Level Controllable Framework for Unsupervised Paraphrase Generation","authors":["Y Chen, H Jiang, L Liu, R Wang, S Shi, R Xu - Findings of the Association for …, 2022"],"snippet":"We present MCPG: a simple and effectiveapproach for controllable unsupervised paraphrase generation, which is also flexible toadapt to specific domains without extra training. MCPG is controllable in different levels: local lexicons, global …","url":["https://aclanthology.org/2022.findings-emnlp.439.pdf"]}
{"year":"2023","title":"MCTS: A Multi-Reference Chinese Text Simplification Dataset","authors":["R Chong, L Lu, L Yang, J Nie, S Zhou, Y Li, E Yang - arXiv preprint arXiv:2306.02796, 2023"],"snippet":"Text simplification aims to make the text easier to understand by applying rewriting transformations. There has been very little research on Chinese text simplification for a long time. The lack of generic evaluation data is an essential reason for this …","url":["https://arxiv.org/pdf/2306.02796"]}
{"year":"2023","title":"Measuring and Evading Turkmenistan's Internet Censorship","authors":["SNVTX Jiang, K Bock, N Feamster, NP Hoang, D Levin - 2023"],"snippet":"… As shown in Figure 2, the payload of our probes contains domains curated from the Citizen Lab lists [5], the full Tranco list [42], and Common Crawl Project [8]. Due to limited resources of our VPS, we opt to probe the frst 10M FQDNs ranked by the …","url":["https://www.cs.umd.edu/users/dml/papers/tm_www23.pdf"]}
{"year":"2023","title":"Measuring and Evading Turkmenistan's Internet Censorship: A Case Study in Large-Scale Measurements of a Low-Penetration Country","authors":["S Nourin, V Tran, X Jiang, K Bock, N Feamster… - arXiv preprint arXiv …, 2023"],"snippet":"… [5], the full Tranco list [42] of most popular websites, and Common Crawl Project [8]. Due to limited resources of our VPS, we opt to probe the first 10M FQDNs ranked by the Common Crawl Project instead of the full list of almost 400M FQDNs. The …","url":["https://arxiv.org/pdf/2304.04835"]}
{"year":"2023","title":"Measuring Gender Bias in West Slavic Language Models","authors":["S Martinková, KSI Augenstein - arXiv preprint arXiv:2304.05783, 2023"],"snippet":"Pre-trained language models have been known to perpetuate biases from the underlying datasets to downstream tasks. However, these findings are predominantly based on monolingual language models for English, whereas there …","url":["https://arxiv.org/pdf/2304.05783"]}
{"year":"2023","title":"Measuring Normative and Descriptive Biases in Language Models Using Census Data","authors":["S Touileb, L Øvrelid, E Velldal - arXiv preprint arXiv:2304.05764, 2023"],"snippet":"We investigate in this paper how distributions of occupations with respect to gender is reflected in pre-trained language models. Such distributions are not always aligned to normative ideals, nor do they necessarily reflect a descriptive assessment …","url":["https://arxiv.org/pdf/2304.05764"]}
{"year":"2023","title":"Medical knowledge-enhanced prompt learning for diagnosis classification from clinical text","authors":["Y Lu, X Zhao, J Wang - Proceedings of the 5th Clinical Natural Language …, 2023"],"snippet":"Artificial intelligence based diagnosis systems have emerged as powerful tools to reform traditional medical care. Each clinician now wants to have his own intelligent diagnostic partner to expand the range of services he can provide. When reading a …","url":["https://aclanthology.org/2023.clinicalnlp-1.33.pdf"]}
{"year":"2023","title":"MedMine: Examining Pre-trained Language Models on Medication Mining","authors":["H Alrdahi, L Han, H Šuvalov, G Nenadic - arXiv preprint arXiv:2308.03629, 2023"],"snippet":"Automatic medication mining from clinical and biomedical text has become a popular topic due to its real impact on healthcare applications and the recent development of powerful language models (LMs). However, fully-automatic …","url":["https://arxiv.org/pdf/2308.03629"]}
{"year":"2023","title":"MEE4 and XLsim: IIIT HYD's Submissions' for WMT23 Metrics Shared Task","authors":["A Mukherjee, M Shrivastava - Proceedings of the Eighth Conference on Machine …, 2023"],"snippet":"This paper presents our contributions to the WMT2023 shared metrics task, consisting of two distinct evaluation approaches: a) Unsupervised Metric (MEE4) and b) Supervised Metric (XLSim). MEE4 represents an unsupervised, reference-based …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.66.pdf"]}
{"year":"2023","title":"Meet in the Middle: A New Pre-training Paradigm","authors":["A Nguyen, N Karampatziakis, W Chen - arXiv preprint arXiv:2303.07295, 2023"],"snippet":"… • CC-Stories contains a subset of CommonCrawl data filtered to match the story-like style of Winograd schemas (31GB). • CC-100 is a dataset extracted from CommonCrawl snapshots between January 2018 and December 2018, filtered to …","url":["https://arxiv.org/pdf/2303.07295"]}
{"year":"2023","title":"MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers","authors":["L Yu, D Simig, C Flaherty, A Aghajanyan, L Zettlemoyer… - arXiv preprint arXiv …, 2023"],"snippet":"Autoregressive transformers are spectacular models for short sequences but scale poorly to long sequences such as high-resolution images, podcasts, code, or books. We proposed Megabyte, a multi-scale decoder architecture that enables end-to-end …","url":["https://arxiv.org/pdf/2305.07185"]}
{"year":"2023","title":"MELA: Multilingual Evaluation of Linguistic Acceptability","authors":["Z Zhang, Y Liu, W Huang, J Mao, R Wang, H Hu - arXiv preprint arXiv:2311.09033, 2023"],"snippet":"Recent benchmarks for Large Language Models (LLMs) have mostly focused on application-driven tasks such as complex reasoning and code generation, and this has led to a scarcity in purely linguistic evaluation of LLMs. Against this background …","url":["https://arxiv.org/pdf/2311.09033"]}
{"year":"2023","title":"Memorization of Named Entities in Fine-Tuned BERT Models","authors":["A Diera, N Lell, A Garifullina, A Scherp - International Cross-Domain Conference for …, 2023"],"snippet":"… During prompt creation, we sampled a string with a character length of 100 either from the Common Crawl dataset (naive prompting) or from the test set (informed prompting). We set the sequence length to 256 tokens. We removed the tokens of …","url":["https://link.springer.com/chapter/10.1007/978-3-031-40837-3_16"]}
{"year":"2023","title":"Method for Sentiment Analysis of Ukrainian-Language Reviews in E-Commerce Using RoBERTa Neural Network","authors":["O Zalutska, M Molchanova, O Sobko, O Mazurets… - 2023"],"snippet":"… This layer is based on the pre-trained model \"xlm_roberta_multi_cased_L-12_H-768_A-12\" [41], which is the result of unsupervised crosslanguage representative training at scale (XLM-RoBERTa) [41] and is pre-trained on 2.5 TB of filtered CommonCrawl …","url":["https://ceur-ws.org/Vol-3387/paper26.pdf"]}
{"year":"2023","title":"Methods for Leveraging Auxiliary Signals for Low-Resource NLP","authors":["X Dong - 2023"],"snippet":"… The standard pre-trained word vectors used for English are the GloVe [69] ones trained on 840 billion tokens of Common Crawl data1, while for other languages, we rely on the Facebook fastText Wikipedia embeddings [76] as input representations …","url":["https://search.proquest.com/openview/6606bd82987b987846b711ddeee598e8/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Methods for Text Generation in NLP","authors":["S Matwin, A Milios, P Prałat, A Soares, F Théberge - Generative Methods for Social …, 2023"],"snippet":"… RoBERTa incorporates far more training data than the original BERT, using the Book Corpus and English Wikipedia datasets from the original paper, but adds several additional datasets for further training (CommonCrawl News, CommonCrawl Stories 6…","url":["https://link.springer.com/chapter/10.1007/978-3-031-33617-1_3"]}
{"year":"2023","title":"Mini But Mighty: Efficient Multilingual Pretraining with Linguistically-Informed Data Selection","authors":["T Ogunremi, D Jurafsky, CD Manning - Findings of the Association for Computational …, 2023"],"snippet":"With the prominence of large pretrained language models, low-resource languages are rarely modelled monolingually and become victims of the “curse of multilinguality” in massively multilingual models. Recently, AfriBERTa showed that training …","url":["https://aclanthology.org/2023.findings-eacl.93.pdf"]}
{"year":"2023","title":"Mining Electronic Health Records: Turning Unstructured Text into Research Data Using Natural Language Processing","authors":["MS Laursen - 2023"],"snippet":"The electronic health record (EHR) contains a detailed account of the patients’ medical history and is an important source of clinical research data. It is estimated that 80% of the information in the EHR is unstructured and this complicates locating …","url":["https://portal.findresearcher.sdu.dk/files/243587681/PhD_dissertation_Martin_Laursen_Redacted.pdf"]}
{"year":"2023","title":"Mining Parallel Sentences from Internet with Multi-view Knowledge Distillation for Low-resource Language Pairs","authors":["S Zhu, S Li, S Gu, L Xu - 2023"],"snippet":"… For the future, we will increase the number of mining data by crawling common crawl platform and focus on more low-resource language pairs. The large amount of parallel data also attracts interesting attention how to use it best. Therefore, we will …","url":["https://www.researchsquare.com/article/rs-2817043/latest.pdf"]}
{"year":"2023","title":"Misinformation Detection in the Wild: News Source Classification as a Proxy for Non-article Texts","authors":["M Bohacek - Proceedings of the Second Workshop on NLP for …, 2022"],"snippet":"… To first obtain URLs of sites with individual articles from those domains, we used the Commoncrawl API 2. We specified for the API to include only articles discovered between January 2019 and September 2021. Once these were obtained, we …","url":["https://aclanthology.org/2022.nlp4pi-1.10.pdf"]}
{"year":"2023","title":"ML and DL-based Phishing Website Detection: The Effects of Varied Size Datasets and Informative Feature Selection Techniques","authors":["K Adane, B Beyene, M Abebe - Journal of Artificial Intelligence and Technology, 2023"],"snippet":"One must interact with a specific webpage or website in order to use the Internet for communication, teamwork, and other productive activities. However, because phishing websites look benign and not all website visitors have the same knowledge …","url":["https://ojs.istp-press.com/jait/article/download/269/274"]}
{"year":"2023","title":"Modeling Brain Representations of Words' Concreteness in Context Using GPT‐2 and Human Ratings","authors":["A Bruera, Y Tao, A Anderson, D Çokal, J Haber… - Cognitive Science, 2023"],"snippet":"The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/cogs.13388"]}
{"year":"2023","title":"Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval","authors":["S Zhang, Y Liang, M Gong, D Jiang, N Duan - arXiv preprint arXiv:2302.01626, 2023"],"snippet":"… (2019), we collect a clean version of Common Crawl (CC) including a 2,500GB multi-lingual corpus covering 108 languages, which adopt the same pre-processing method as XLMR (Conneau et al., 2019). Note that we only train on CC without any …","url":["https://arxiv.org/pdf/2302.01626"]}
{"year":"2023","title":"Modelling an Efficient URL Phishing Detection Approach Based on a Dense Network Model.","authors":["AA Tenis, R Santhosh - Computer Systems Science & Engineering, 2023"],"snippet":"… The PhishTank provides the URLs for phishing to be gathered, and the Common Crawl provides the legal URLs. The LSTM technique … The repositories of Common Crawl and PhishTank provide the dataset to be gathered. A deep belief network (DBN) …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=02676192&AN=169779920&h=WGjAKpK7ACB1ZcUfp8Ikhm9IcDPjsbjptgyhA5ityW47Z2oYK4JmZTEMhj6t1UhLOFgbraBWyMgS1NID6mz%2BcA%3D%3D&crl=c"]}
{"year":"2023","title":"Modern Applications With a Focus on Training ChatGPT and GPT Models: Exploring Generative AI and NLP","authors":["I Kondurkar, A Raj, D Lakshmi - Advanced Applications of Generative AI and Natural …, 2024"],"snippet":"Generative AI (GAI) and natural language processing (NLP) have emerged as the most exciting and rapidly growing fields in artificial intelligence (AI). This book chapter provides a comprehensive exploration of the advanced applications of GAI …","url":["https://www.igi-global.com/chapter/modern-applications-with-a-focus-on-training-chatgpt-and-gpt-models/335839"]}
{"year":"2023","title":"Modular DiffPruning for Bias Mitigation","authors":["J KEPLER"],"snippet":"… They can leverage unlabelled text data which is available in large amounts on the internet and is collected by projects such as common crawl.Unsurprisingly raw text data crawled from the internet often contains bias towards different groups [3, 4] …","url":["https://epub.jku.at/obvulihs/download/pdf/8342002?originalFilename=true"]}
{"year":"2023","title":"ModuleFormer: Learning Modular Large Language Models From Uncurated Data","authors":["Y Shen, Z Zhang, T Cao, S Tan, Z Chen, C Gan - arXiv preprint arXiv:2306.04640, 2023"],"snippet":"Large Language Models (LLMs) have achieved remarkable results. But existing models are expensive to train and deploy, and it is also difficult to expand their knowledge beyond pre-training data without forgetting previous knowledge. This …","url":["https://arxiv.org/pdf/2306.04640"]}
{"year":"2023","title":"MONITORING FILE FORMAT OBSOLESCENCE IN REPOSITORIES: An applied method","authors":["S Alloing - iPRES 2023, 2023"],"snippet":"… Common Crawl and data from different institutional repositories (Netherlands Institute for Sound and Vision and Data Archiving and Networked Services (DANS)). The Common Crawl … and this prevents the need to process all the Common Crawl …","url":["https://www.ideals.illinois.edu/items/128320/bitstreams/429005/object"]}
{"year":"2023","title":"Mono-and Multilingual GPT-3 Models for Hungarian","authors":["ZG Yang, LJ Laki, T Váradi, G Prószéky - … Conference on Text, Speech, and Dialogue, 2023"],"snippet":"… Common Crawl (CC): Most of our Hungarian text was collected from the Common Crawl database. Since the Webcorpus 2.0 contains text only until April of 2019, we collected the data that was created afterwards. For downloading and boilerplate-cleaning …","url":["https://link.springer.com/chapter/10.1007/978-3-031-40498-6_9"]}
{"year":"2023","title":"Monolingual and Cross-Lingual Survey Response Annotation","authors":["Y Zhao - 2023"],"snippet":"… This model is pre-trained on the CommonCrawl data of 100 languages using multilingual MLM, with a vocabulary size 250k. It outperforms state-of-the-art cross-lingual benchmark models, including mBERT, in cross-language classification, sequence …","url":["https://www.diva-portal.org/smash/get/diva2:1814552/FULLTEXT01.pdf"]}
{"year":"2023","title":"Monolingual, multilingual and cross-lingual code comment classification","authors":["M Kostić, V Batanović, B Nikolić - Engineering Applications of Artificial Intelligence, 2023"],"snippet":"Code comments are one of the most useful forms of documentation and metadata for understanding software implementation. Previous research on code comment classification has focused only on comments in English, typically extracted from a …","url":["https://www.sciencedirect.com/science/article/pii/S0952197623006693"]}
{"year":"2023","title":"MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining","authors":["J Portes, AR Trott, S Havens, D King, A Venigalla… - Thirty-seventh Conference …, 2023"],"snippet":"Although BERT-style encoder models are heavily used in NLP research, many researchers do not pretrain their own BERTs from scratch due to the high cost of training. In the past half-decade since BERT first rose to prominence, many …","url":["https://openreview.net/pdf?id=5zipcfLC2Z"]}
{"year":"2023","title":"MosaicBERT: How to Train BERT with a Lunch Money Budget","authors":["J Portes, AR Trott, S Havens, D King, A Venigalla… - Workshop on Efficient …, 2023"],"snippet":"Although BERT-style encoder models are heavily used in NLP research, many researchers do not pretrain their own BERTs from scratch due to the high cost of training. In the past half-decade since BERT first rose to prominence, many …","url":["https://openreview.net/pdf?id=WH1S0gonzR"]}
{"year":"2023","title":"mPLM-Sim: Unveiling Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models","authors":["P Lin, C Hu, Z Zhang, AFT Martins, H Schütze - arXiv preprint arXiv:2305.13684, 2023"],"snippet":"Recent multilingual pretrained language models (mPLMs) have been shown to encode strong language-specific signals, which are not explicitly provided during pretraining. It remains an open question whether it is feasible to employ mPLMs to …","url":["https://arxiv.org/pdf/2305.13684"]}
{"year":"2023","title":"mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video","authors":["H Xu, Q Ye, M Yan, Y Shi, J Ye, Y Xu, C Li, B Bi, Q Qian… - arXiv preprint arXiv …, 2023"],"snippet":"Recent years have witnessed a big convergence of language, vision, and multi-modal pretraining. In this work, we present mPLUG-2, a new unified paradigm with modularized design for multi-modal pretraining, which can benefit from modality …","url":["https://arxiv.org/pdf/2302.00402"]}
{"year":"2023","title":"muGen: Generative AI as Machinic Exploration of Cultural Archives","authors":["Y Yu - 2023"],"snippet":"In recent years, generative AI has quickly become a new creative and artistic tool that could challenge our understanding of the creative process and the role of the machine. Despite having exhibited visually promising results, images generated by …","url":["https://www.diva-portal.org/smash/get/diva2:1813415/FULLTEXT01.pdf"]}
{"year":"2023","title":"Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams","authors":["M Tavakoli, R Chandra, F Tian, C Bravo - arXiv preprint arXiv:2304.10740, 2023"],"snippet":"Knowing which factors are significant in credit rating assignment leads to better decision-making. However, the focus of the literature thus far has been mostly on structured data, and fewer studies have addressed unstructured or multi-modal …","url":["https://arxiv.org/pdf/2304.10740"]}
{"year":"2023","title":"MultiFin: A Dataset for Multilingual Financial NLP","authors":["R Jørgensen, O Brandt, M Hartmann, X Dai, C Igel… - Findings of the Association …, 2023"],"snippet":"… Embedding alignment We map monolingual fasttext embeddings trained on Wikipedia and Commoncrawl into a shared space using RCSLS, by computing pairwise mappings between source languages and English as a target language. As …","url":["https://aclanthology.org/2023.findings-eacl.66.pdf"]}
{"year":"2023","title":"Multilanguage Word Embeddings for Social Scientists: Estimation, Inference and Validation Resources for 157 Languages","authors":["PL Rodriguez, A Spirling, BM Stewart, EM Wirsching"],"snippet":"… from Common Crawl and Wikipedia. A strength of the fastText model is that it uses subword … Common Crawl includes a large number of typos and very rare terms (plus many English loan … Beyond this potential for noise, note also that Common Crawl …","url":["https://alcembeddings.org/assets/img/RSSW_paper_June_2023.pdf"]}
{"year":"2023","title":"MultiLegalPile: A 689GB Multilingual Legal Corpus","authors":["J Niklaus, V Matoshi, M Stürmer, I Chalkidis, DE Ho - arXiv preprint arXiv:2306.02069, 2023"],"snippet":"… The Common Crawl corpus is a publicly available multilingual dataset of scraped web pages, … As a result, utilizing the Common Crawl dataset necessitates additional post-filtering and … 2020a) performed several cleaning steps on the April …","url":["https://arxiv.org/pdf/2306.02069"]}
{"year":"2023","title":"Multilingual and Multi-domain Opinion Mining","authors":["L JACQMIN - 2023"],"snippet":"Everyday, multinational companies receive large amounts of customer feedback. Valuable insights can be extracted from it to address customers’ needs. This textual feedback can span various languages and domains. Due to this variability, generic …","url":["https://jacqle.github.io/assets/pdf/Masters_Thesis_Leo_Jacqmin.pdf"]}
{"year":"2023","title":"Multilingual Coarse Political Stance Classification of Media. The Editorial Line of a ChatGPT and Bard Newspaper","authors":["C España-Bonet - arXiv preprint arXiv:2310.16269, 2023"],"snippet":"Neutrality is difficult to achieve and, in politics, subjective. Traditional media typically adopt an editorial line that can be used by their potential readers as an indicator of the media bias. Several platforms currently rate news outlets according to their …","url":["https://arxiv.org/pdf/2310.16269"]}
{"year":"2023","title":"Multilingual Jailbreak Challenges in Large Language Models","authors":["Y Deng, W Zhang, SJ Pan, L Bing - arXiv preprint arXiv:2310.06474, 2023"],"snippet":"… (2023), we determine the resource levels for each language by utilizing the data ratio from the CommonCrawl corpus1, which serves as the primary dataset for most LLMs’ pre-training. Specifically, a language is categorized as high-resource if its …","url":["https://arxiv.org/pdf/2310.06474"]}
{"year":"2023","title":"Multilingual Language Models are not Multicultural: A Case Study in Emotion","authors":["S Havaldar, S Rai, B Singhal, LLSC Guntuku, L Ungar - arXiv preprint arXiv …, 2023"],"snippet":"Emotions are experienced and expressed differently across the world. In order to use Large Language Models (LMs) for multilingual tasks that require emotional sensitivity, LMs must reflect this cultural variation in emotion. In this study, we …","url":["https://arxiv.org/pdf/2307.01370"]}
{"year":"2023","title":"Multilingual Natural Language Processing Model for Radiology Reports The Summary is all you need!","authors":["M Lindo, AS Santos, A Ferreira, J Li, G Luijten… - arXiv preprint arXiv …, 2023"],"snippet":"… guages gathered from the publicly available Common Crawl Web Scrape. The mT5 model offers five model sizes, one of which is the base size with 580M parameters, and was used in this project. One difference between T5 and mT5 is that mT5 was …","url":["https://www.researchgate.net/profile/Mariana-Lindo/publication/374414168_Multilingual_Natural_Language_Processing_Model_for_Radiology_Reports_-_The_Summary_is_all_you_need/links/651c3ce13ab6cb4ec6b76a5e/Multilingual-Natural-Language-Processing-Model-for-Radiology-Reports-The-Summary-is-all-you-need.pdf"]}
{"year":"2023","title":"Multilingual semantic distance: Automatic verbal creativity assessment in many languages.","authors":["JD Patterson, HM Merseal, DR Johnson, S Agnoli… - Psychology of Aesthetics …, 2023"],"snippet":"… MBERT is trained on the 104 languages with the largest Wikipedia databases, while XLMR is trained on cleaned CommonCrawl data that covers 100 languages. CommonCrawl is an archive of steadily increasing size that is produced by an …","url":["https://psycnet.apa.org/record/2024-07870-002"]}
{"year":"2023","title":"Multilingual Simplification of Medical Texts","authors":["S Joseph, K Kazanas, K Reina, VJ Ramanathan, W Xu… - arXiv preprint arXiv …, 2023"],"snippet":"… 2022) used Common Crawl to mine millions of sequence pairs in English, Spanish, and French. The significant difference between MUSS and our dataset is MUSS’s lack of cross-lingual alignment, ie, alignment of sequence pairs from one language …","url":["https://arxiv.org/pdf/2305.12532"]}
{"year":"2023","title":"Multilingual Summarization with Factual Consistency Evaluation","authors":["R Aharoni, S Narayan, J Maynez, J Herzig, E Clark… - Findings of the Association …, 2023"],"snippet":"Abstractive summarization has enjoyed renewed interest in recent years, thanks to pre-trained language models and the availability of large-scale datasets. Despite promising results, current models still suffer from generating factually inconsistent …","url":["https://aclanthology.org/2023.findings-acl.220.pdf"]}
{"year":"2023","title":"Multilingual text categorization and sentiment analysis: a comparative analysis of the utilization of multilingual approaches for classifying twitter data","authors":["G Manias, A Mavrogiorgou, A Kiourtis, C Symvoulidis… - Neural Computing and …, 2023"],"snippet":"… XLM-RoBERTa (XLM-R) XLM-RoBERTa (XLM-R) is a multilingual masked language model introduced by authors in [21] that trained on 2.5 TB of newly created clean CommonCrawl data in 100 languages. It is an update to the original XLM-100 …","url":["https://link.springer.com/article/10.1007/s00521-023-08629-3"]}
{"year":"2023","title":"Multilingual Text Representation","authors":["F Faisal - arXiv preprint arXiv:2309.00949, 2023"],"snippet":"Modern NLP breakthrough includes large multilingual models capable of performing tasks across more than 100 languages. State-of-the-art language models came a long way, starting from the simple one-hot representation of words capable of …","url":["https://arxiv.org/pdf/2309.00949"]}
{"year":"2023","title":"Multilingual, monolingual and mono-dialectal transfer learning for Moroccan Arabic sentiment classification","authors":["N Boudad, R Faizi, R Oulad Haj Thami - Social Network Analysis and Mining, 2024"],"snippet":"Transfer learning has recently proven to be very powerful in diverse natural language processing (NLP) tasks such as Machine translation, Sentiment Analysis, and Question/Answering. In this work, we investigate the use of transfer learning (TL) …","url":["https://link.springer.com/article/10.1007/s13278-023-01159-9"]}
{"year":"2023","title":"Multilinguality in Language Models","authors":["I Partalas - 2023"],"snippet":"• Increasing batch size and training time enhances model performance• Tokenization tools used by mBERT and XLM-100 make these models more difficult to use on raw text• No performance loss for models trained with SPM, compared to …","url":["https://cis.lmu.de/~yehao/teaching/gpts/multilinguality.pdf"]}
{"year":"2023","title":"Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved With Text","authors":["W Zhu, J Hessel, A Awadalla, SY Gadre, J Dodge… - arXiv preprint arXiv …, 2023"],"snippet":"… We first retrieve the original webpages for each document in the c4-en dataset from the Common Crawl version 2019-18, which is the default version for c4. Next, we extract the URLs for downloadable images from the raw WAT files. We restrict the …","url":["https://arxiv.org/pdf/2304.06939"]}
{"year":"2023","title":"Multimodal Coreference Resolution","authors":["AS Varela, K Knill"],"snippet":"In a situated dialog system, multimodal coreference resolution is the task of identifying which entity the user is referring to within a certain context defined by both natural language and visual modalities. This is a crucial task to tackle in order …","url":["https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/multimodal_coreference_resolution_reduced.pdf"]}
{"year":"2023","title":"Multimodal text summarization with evaluation approaches","authors":["AFUR Khilji, U Sinha, P Singh, A Ali, SR Laskar… - Sādhanā, 2023"],"snippet":"Multimodal text summarization is a complex and challenging task in the field of natural language processing. Its objective is to use a combination of features from various modalities to create a concise yet informative summary from a given set of …","url":["https://link.springer.com/article/10.1007/s12046-023-02284-z"]}
{"year":"2023","title":"MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark","authors":["D Macko, R Moro, A Uchendu, JS Lucas, M Yamashita… - arXiv preprint arXiv …, 2023"],"snippet":"… We have used on-request author-provided processed data as well as CommonCrawl based links published in the GitHub repository. Both sources result in per-language … XLM-RoBERTa16 is a pre-trained on 2.5TB of filtered …","url":["https://arxiv.org/pdf/2310.13606"]}
{"year":"2023","title":"MultiVENT: Multilingual Videos of Events with Aligned Natural Text","authors":["K Sanders, D Etter, R Kriz, B Van Durme - arXiv preprint arXiv:2307.03153, 2023"],"snippet":"… To incorporate multilinguality into the model’s frame-level features, we use a ViT architecture trained with a contrastive objective over multilingual image-caption pairs from the LAION-5B dataset [42], which is constructed from the Common Crawl …","url":["https://arxiv.org/pdf/2307.03153"]}
{"year":"2023","title":"Murreviikko-A Dialectologically Annotated and Normalized Dataset of Finnish Tweets","authors":["O Kuparinen - Tenth Workshop on NLP for Similar Languages …, 2023"],"snippet":"This paper presents Murreviikko, a dataset of dialectal Finnish tweets which have been dialectologically annotated and manually normalized to a standard form. The dataset can be used as a test set for dialect identification and dialect-to-standard …","url":["https://aclanthology.org/2023.vardial-1.3.pdf"]}
{"year":"2023","title":"Mutation-Based Adversarial Attacks on Neural Text Detectors","authors":["G Liang, J Guerrero, I Alsmadi - arXiv preprint arXiv:2302.05794, 2023"],"snippet":"Neural text detectors aim to decide the characteristics that distinguish neural (machine-generated) from human texts. To challenge such detectors, adversarial attacks can alter the statistical characteristics of the generated text, making the detection task more and …","url":["https://arxiv.org/pdf/2302.05794"]}
{"year":"2023","title":"NAIL: Lexical Retrieval Indices with Efficient Non-Autoregressive Decoders","authors":["LB Soares, D Gillick, JR Cole, T Kwiatkowski - arXiv preprint arXiv:2305.14499, 2023"],"snippet":"Neural document rerankers are extremely effective in terms of accuracy. However, the best models require dedicated hardware for serving, which is costly and often not feasible. To avoid this serving-time requirement, we present a method of …","url":["https://arxiv.org/pdf/2305.14499"]}
{"year":"2023","title":"Named Entity Recognition for De-identifying Real-World Health Records in Spanish","authors":["G López-García, FJ Moreno-Barea, H Mesa, JM Jerez… - International Conference on …, 2023"],"snippet":"… XLM-R: this multilingual version of the RoBERTa architecture [18] was pretrained on a massive 2.4TB CommonCrawl Corpus in 100 languages [2], using a large multilingual vocabulary of \\(\\sim \\)250K subwords. We experimented with both the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-36024-4_17"]}
{"year":"2023","title":"Named entity recognition in resumes","authors":["E Kesim, A Deliahmetoglu - arXiv preprint arXiv:2306.13062, 2023"],"snippet":"Named entity recognition (NER) is used to extract information from various documents and texts such as names and dates. It is important to extract education and work experience information from resumes in order to filter them. Considering …","url":["https://arxiv.org/pdf/2306.13062"]}
{"year":"2023","title":"Named Entity-Oriented Sentiment Analysis with text2text Generation Approach","authors":["I Moloshnikov, M Skorokhodov, A Naumov, R Rybka… - Proceedings of the …, 2023"],"snippet":"… The CommonCrawl data contains text in 100 languages, of which the Russian language is one of the most representative. … Wikipedia, books, news, and CommonCrawl texts were used to train them. The model dictionary size is 32101 …","url":["https://www.dialog-21.ru/media/5916/moloshnikoviplusetal113.pdf"]}
{"year":"2023","title":"Natural Language Inference for Arabic using Recurrent Neural Network and Word Embedding","authors":["M Bensghaier, W Bakari, M Neji - 2022 IEEE/ACS 19th International Conference on …, 2022"],"snippet":"The Natural Language Inference (NLI) task is a field of Natural Language Processing (NLP) in which researchers try to find ways to decide about the inference relation between two sentences. In this paper, we present an early version of an …","url":["https://ieeexplore.ieee.org/abstract/document/10017722/"]}
{"year":"2023","title":"Natural language processing deep learning models for the differential between high-grade gliomas and metastasis: what if the key is how we report them?","authors":["T Martín-Noguerol, P López-Úbeda, A Pons-Escoda… - European Radiology, 2023"],"snippet":"Objectives The differential between high-grade glioma (HGG) and metastasis remains challenging in common radiological practice. We compare different natural language processing (NLP)–based deep learning models to assist radiologists …","url":["https://link.springer.com/article/10.1007/s00330-023-10202-4"]}
{"year":"2023","title":"Natural Language Processing For Automatic text summarization [Datasets]-Survey","authors":["AA AL-Banna, AK AL-Mashhadany - Wasit Journal of Computer and Mathematics …, 2022"],"snippet":"… These stories are based on sources mentioned by WCEP editors and automatically collected from Common Crawl News and supplemented with items acquired automatically from t (WCEP) [14]. The best result in the dataset shown in [15] …","url":["https://wjcm.uowasit.edu.iq/index.php/wjcm/article/download/72/68"]}
{"year":"2023","title":"Natural Language Processing with Generative AI Models: A Methodological Approach for Their Application","authors":["S Strippoli - 2023"],"snippet":"… OpenAI trained eight different models of varying sizes, ranging from 125 million to 175 billion parameters, using a dataset refined from the CommonCrawl, which contained nearly a trillion words of … For GPT-3, the size refers to the filtered …","url":["https://webthesis.biblio.polito.it/secure/28973/1/tesi.pdf"]}
{"year":"2023","title":"Natural Language Processing: Practical Approach","authors":["SM Basha, AS Fathima - 2023"],"snippet":"… Using External Data: There are several online resources that provide large text corpora such as Project Gutenberg, Common Crawl and Wikipedia. These resources can be accessed using the appropriate API and downloaded locally for further analysis. …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=ciOwEAAAQBAJ&oi=fnd&pg=PA1&dq=commoncrawl&ots=s-uWXu426A&sig=EnVdKElz2TIaNnf_YbXj0JBhNZE"]}
{"year":"2023","title":"Natural Language-Assisted Sign Language Recognition","authors":["R Zuo, F Wei, B Mak - arXiv preprint arXiv:2303.12080, 2023"],"snippet":"… Concretely, given a sign vocabulary containing N glosses, we leverage fastText [38] pretrained on Common Crawl to extract a 300-d feature for each gloss. We use E ∈ RN×300 to denote the N gloss features. Language-Aware Label Smoothing and …","url":["https://arxiv.org/pdf/2303.12080"]}
{"year":"2023","title":"Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework","authors":["J Zhang, X Zhang, X Zhang, D Hong, RK Gupta… - 2023"],"snippet":"Traditional federated classification methods, even those designed for non-IID clients, assume that each client annotates its local data with respect to the same universal class set. In this paper, we focus on a more general yet practical setting, non-identical …","url":["http://mesl.ucsd.edu/pubs/Jiayun_KDD2023_FEDALIGN.pdf"]}
{"year":"2023","title":"Navigating the Ethical Landmines of ChatGPT: Implications of Intelligent Chatbots in Plastic Surgery Clinical Practice","authors":["NC Oleck, HI Naga, DS Nichols, MX Morris, B Dhingra… - Plastic and Reconstructive …, 2023"],"snippet":"… The large dataset used to train ChatGPT is derived from “internet dumps” obtained via web scraping from open source datasets such as Common Crawl and OpenWebText. These datasets are composed of data sourced from over 20 million …","url":["https://journals.lww.com/prsgo/fulltext/2023/09000/navigating_the_ethical_landmines_of_chatgpt_.42.aspx?context=latestarticles"]}
{"year":"2023","title":"Navigating the generative AI era: Introducing the AI assessment scale for ethical GenAI assessment","authors":["M Perkins, L Furze, J Roe, J MacVaugh - arXiv preprint arXiv:2312.07086, 2023"],"snippet":"Recent developments in Generative Artificial Intelligence (GenAI) have created a paradigm shift in multiple areas of society, and the use of these technologies is likely to become a defining feature of education in coming decades. GenAI offers …","url":["https://arxiv.org/pdf/2312.07086"]}
{"year":"2023","title":"Negation and speculation processing: A study on cue-scope labelling and assertion classification in Spanish clinical text","authors":["N Perez, M Cuadros, G Rigau - Artificial Intelligence in Medicine, 2023"],"snippet":"Natural Language Processing (NLP) based on new deep learning technology is contributing to the emergence of powerful solutions that help healthcare providers and researchers discover valuable patterns within insurmountable volumes of health …","url":["https://www.sciencedirect.com/science/article/pii/S0933365723001963"]}
{"year":"2023","title":"Negativity spreads faster: A large-scale multilingual twitter analysis on the role of sentiment in political communication","authors":["D Antypas, A Preece, J Camacho-Collados - Online Social Networks and Media, 2023"],"snippet":"Social media has become extremely influential when it comes to policy making in modern societies, especially in the western world, where platforms such as Twitter allow users to follow politicians, thus making citizens more involved in political …","url":["https://www.sciencedirect.com/science/article/pii/S2468696423000010"]}
{"year":"2023","title":"Nested Named-Entity Recognition in Multilingual Code-Switched NLP Check for updates","authors":["A Patil, U Kolhe - Big Data, Machine Learning, and Applications …, 2024"],"snippet":"… OSCAR Open Super-large Crawled Aggregated coRpus (OSCAR) is a huge multilingual corpus obtained by language classification and filtering of Common Crawl corpus. The dataset contains 166 languages in total. We are using this dataset for adaptive …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=IrrmEAAAQBAJ&oi=fnd&pg=PA368&dq=commoncrawl&ots=mzlcvjaWFp&sig=UAZ6zHL60TQpG3gRkxgshDExQjw"]}
{"year":"2023","title":"Netizens, Academicians, and Information Professionals' Opinions About AI With Special Reference To ChatGPT","authors":["A Subaveerapandiyan, A Vinoth, N Tiwary - Library Philosophy and Practice (e …, 2023","N Tiwary - arXiv preprint arXiv:2302.07136, 2023"],"snippet":"This study aims to understand the perceptions and opinions of academicians towards ChatGPT-3 by collecting and analyzing social media comments, and a survey was conducted with library and information science professionals. The …","url":["https://arxiv.org/pdf/2302.07136","https://hcommons.org/deposits/view/hc:52298/CONTENT/netizens-academicians-and-information-professionals-opinions-about-ai-with-special-reference-to-chatgpt.pdf/"]}
{"year":"2023","title":"Neural correlates of object-extracted relative clause processing across English and Chinese","authors":["D Dunagan, M Stanojević, M Coavoux, S Zhang… - Neurobiology of Language"],"snippet":"Are the brain bases of language comprehension the same across all human languages, or do these bases vary in a way that corresponds to differences in linguistic typology? English and Mandarin Chinese attest such a typological …","url":["https://direct.mit.edu/nol/article-pdf/doi/10.1162/nol_a_00110/2112616/nol_a_00110.pdf"]}
{"year":"2023","title":"Neural Data Search for Table Augmentation","authors":["A Brinkmann - 2023"],"snippet":"… WDC table corpus2 consists of 4.2 million relational tables generated by extracting schema.org3 annotations from the Common Crawl and grouping the annotations by class and host. All tables in this corpus share a common schema. By …","url":["https://ceur-ws.org/Vol-3379/PhDWorkshop_2023_brinkmann-paper.pdf"]}
{"year":"2023","title":"Neural Embeddings for Web Testing","authors":["A Stocco, A Willi, LLL Starace, M Biagiola, P Tonella - arXiv preprint arXiv …, 2023"],"snippet":"Web test automation techniques employ web crawlers to automatically produce a web app model that is used for test generation. Existing crawlers rely on app-specific, threshold-based, algorithms to assess state equivalence. Such algorithms are hard …","url":["https://arxiv.org/pdf/2306.07400"]}
{"year":"2023","title":"Neural Language Generation for Content Adaptation: Explainable, Efficient Low-Resource Text Simplification and Evaluation","authors":["GC Garbacea - 2023"],"snippet":"There are rich opportunities to reduce the language complexity of professional content (either human-written or computer-generated) and make it accessible to a broad audience. As a sub-task of natural language generation (NLG), text …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/178028/garbacea_1.pdf?sequence=1"]}
{"year":"2023","title":"Neural machine translation for in‐text citation classification","authors":["I Safder, M Ali, NR Aljohani, R Nawaz, SU Hassan - Journal of the Association for …"],"snippet":"The quality of scientific publications can be measured by quantitative indices such as the h‐index, Source Normalized Impact per Paper, or g‐index. However, these measures lack to explain the function or reasons for citations and the context of …","url":["https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/asi.24817"]}
{"year":"2023","title":"Neural Machine Translation For Low Resource Languages","authors":["C Utsa, G Vakul, K Parvathy, RG Kannan","V Goyle, K Goyle, P Krishnaswamy, KG Ravikumar… - arXiv preprint arXiv …, 2023"],"snippet":"… It is trained on the monolingual common crawl corpus for 25 languages (CC25). The text corpus is further tokenized using the sentence-piece model (SPM) [6] which provides both subword tokenization and unigram language modelling additionally …","url":["https://arxiv.org/pdf/2304.07869","https://www.academia.edu/download/102811574/TeamT_Project_Report_1.pdf"]}
{"year":"2023","title":"Neural machine translation to local languages","authors":["V Shah, S Valiullah, MY Makwana"],"snippet":"Neural Machine Translation (NMT) has demonstrated significant potential in facilitating communication across language barriers. However, adapting NMT systems to low-resource local languages poses significant challenges due to the …","url":["https://www.researchgate.net/profile/Vaibhav-Shah-36/publication/369857893_Neural_machine_translation_to_local_languages/links/642fe1044e83cd0e2f979230/Neural-machine-translation-to-local-languages.pdf"]}
{"year":"2023","title":"Neural Machine Translation, Large Language Models and Literary Translation: The Story So Far","authors":["D Kenny, D Hansen - ITIA CPD, 2023"],"snippet":"We understand ‘literary machine translation’as an emerging interdisciplinary field that embraces a range of phenomena related to the application of MT to the translation of literary texts. It touches upon or intersects with, among other areas: ● …","url":["https://orbi.uliege.be/bitstream/2268/302554/1/presentation_ITIA_kenny_hansen.pdf"]}
{"year":"2023","title":"Neural semantic tagging for natural language-based search in building information models: Implications for practice","authors":["M Shahinmoghadam, SE Kahou, A Motamedi - Computers in Industry, 2024"],"snippet":"While the adoption of open Building Information Modeling (open BIM) standards continues to grow, the inherent complexity and multifaceted nature of the built asset lifecycle data present a critical bottleneck for effective information retrieval. To …","url":["https://www.sciencedirect.com/science/article/pii/S0166361523002130"]}
{"year":"2023","title":"NeuralMind-UNICAMP at 2022 TREC NeuCLIR: Large Boring Rerankers for Cross-lingual Retrieval","authors":["V Jeronymo, R Lotufo, R Nogueira - arXiv preprint arXiv:2303.16145, 2023"],"snippet":"This paper reports on a study of cross-lingual information retrieval (CLIR) using the mT5-XXL reranker on the NeuCLIR track of TREC 2022. Perhaps the biggest contribution of this study is the finding that despite the mT5 model being fine-tuned …","url":["https://arxiv.org/pdf/2303.16145"]}
{"year":"2023","title":"Neuroinformatics, Neural Networks and Neurocomputers for Computational Intelligence","authors":["NK Kasabov - Neuroinformatics, 2023"],"snippet":"1. Learning from (big) data-> neural networks and deep NN 2. Explainability (extracting rules, associations)(explainable AI)→ fuzzy logic/neuro-fuzzy systems 3. Evolvability→ evolving connectionist systems (ECOS) and brain-inspired SNN (NeuCube). 4 …","url":["http://conf.uni-obuda.hu/saci2023/SACI2023PlenaryPaper_NKasabov_presentation.pdf"]}
{"year":"2023","title":"New Challenges in Official Statistics: Big Data Analytics and Multi-level Product Classification of Web Scraped Data","authors":["JFU Machado - 2023"],"snippet":"The surge in internet usage has significantly amplified data generation, paving the way for researchers and policymakers to gain in-depth and granular insights about society. This shift has transformed data collection methodologies, fostering the …","url":["https://repositorio-aberto.up.pt/bitstream/10216/151290/2/635323.pdf"]}
{"year":"2023","title":"New Evaluation Metrics Capture Quality Degradation due to LLM Watermarking","authors":["K Singh, J Zou - arXiv preprint arXiv:2312.02382, 2023"],"snippet":"With the increasing use of large-language models (LLMs) like ChatGPT, watermarking has emerged as a promising approach for tracing machine-generated content. However, research on LLM watermarking often relies on simple perplexity …","url":["https://arxiv.org/pdf/2312.02382"]}
{"year":"2023","title":"New models developed for detection of misconceptions in physics with artificial intelligence","authors":["MU Demirezen, O Yilmaz, E Ince - Neural Computing and Applications, 2023"],"snippet":"Students’ misconceptions of various topics in physics have been investigated by many researchers. The detection of misconceptions is very difficult and takes a long time as a human being. Our aim in the study carried out is to determine the …","url":["https://link.springer.com/article/10.1007/s00521-023-08414-2"]}
{"year":"2023","title":"nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Models","authors":["M Cosler, C Hahn, D Mendoza, F Schmitt, C Trippel - arXiv preprint arXiv:2303.04864, 2023"],"snippet":"A rigorous formalization of desired system requirements is indispensable when performing any verification task. This often limits the application of verification techniques, as writing formal specifications is an error-prone and time-consuming …","url":["https://arxiv.org/pdf/2303.04864"]}
{"year":"2023","title":"NLP Meets Agronomy: Document Classification for Plant Health Surveillance","authors":["LAV Reina, R Bossy - 2023"],"snippet":"In the field of Plant Health Epidemiological Surveillance, accurately analyzing written reports of events affecting agriculture is crucial. This master’s thesis in Natural Language Processing leverages the power of Automatic Text Classification …","url":["https://hal.science/hal-04223051/document"]}
{"year":"2023","title":"NLP-Based Automated Conspiracy Detection for Massive Twitter Datasets","authors":["R Akbari - 2023"],"snippet":"The COVID-19 pandemic, which affected societies worldwide, and many were compelled to shut down, also affected social media platforms like Twitter. The COVID-19-related misinformation on Twitter covered various topics and contained many competing …","url":["https://www.duo.uio.no/bitstream/handle/10852/103705/17/MasterThesis_RohullahAkbari.pdf"]}
{"year":"2023","title":"NosWalker: A Decoupled Architecture for Out-of-Core Random Walk Processing","authors":["S Wang, M Zhang, K Yang, K Chen, S Ma, J Jiang… - Proceedings of the 28th …, 2023"],"snippet":"Out-of-core random walk system has recently attracted a lot of attention as an economical way to run billions of walkers over large graphs. However, existing out-of-core random walk systems are all built upon general out-of-core graph processing …","url":["https://dl.acm.org/doi/abs/10.1145/3582016.3582025"]}
{"year":"2023","title":"Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting","authors":["H Huang, T Tang, D Zhang, WX Zhao, T Song, Y Xia… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs) demonstrate impressive multilingual capability, but their performance varies substantially across different languages. In this work, we introduce a simple yet effective method, called cross-lingual-thought prompting (XLT) …","url":["https://arxiv.org/pdf/2305.07004"]}
{"year":"2023","title":"Nougat: Neural Optical Understanding for Academic Documents","authors":["L Blecher, G Cucurull, T Scialom, R Stojnic - arXiv preprint arXiv:2308.13418, 2023"],"snippet":"Scientific knowledge is predominantly stored in books and scientific journals, often in the form of PDFs. However, the PDF format leads to a loss of semantic information, particularly for mathematical expressions. We propose Nougat (Neural Optical …","url":["https://arxiv.org/pdf/2308.13418"]}
{"year":"2023","title":"NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation","authors":["P West, RL Bras, T Sorensen, BY Lin, L Jiang, X Lu… - arXiv preprint arXiv …, 2023"],"snippet":"We present NovaCOMET, an open commonsense knowledge model, that combines the best aspects of knowledge and general task models. Compared to previous knowledge models, NovaCOMET allows open-format relations enabling direct …","url":["https://arxiv.org/pdf/2312.05979"]}
{"year":"2023","title":"Novel embeddings improve the prediction of risk perception","authors":["Z Hussain, DU Wulff, R Mata - 2023"],"snippet":"… fastText was trained on the Common Crawl, a corpus of web pages that is more diverse and with 600B tokens considerably larger than the … GloVe was trained on a slightly larger version of the Common Crawl than fastText comprising 804B. We …","url":["https://psyarxiv.com/yrjfb/download?format=pdf"]}
{"year":"2023","title":"Ntcir-17 mednlp-sc social media adverse drug event detection: Subtask overview","authors":["S Wakamiya, LK Pereira, L Raithel, HS Yeh, P Han… - Proceedings of the 17th …, 2023"],"snippet":"… It is pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. XLM-R has been shown to perform particularly well in low-resource languages, such as Swahili and Urdu. We use the XLM-R base model released by the authors. …","url":["http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings17/pdf/ntcir/01-NTCIR17-OV-MEDNLP-WakamiyaS.pdf"]}
{"year":"2023","title":"Oasis: Data Curation and Assessment System for Pretraining of Large Language Models","authors":["T Zhou, Y Chen, P Cao, K Liu, J Zhao, S Liu - arXiv preprint arXiv:2311.12537, 2023"],"snippet":"… Aside from introducing Oasis, we demonstrate a complete case that utilizes this platform to build a high-quality and high-diversity Common Crawl corpus. Meanwhile, we holistic assess the corpus in the different development stages. The assessments …","url":["https://arxiv.org/pdf/2311.12537"]}
{"year":"2023","title":"OBELISC: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents","authors":["H Laurençon, L Saulnier, L Tronchon, S Bekman… - arXiv preprint arXiv …, 2023"],"snippet":"… We introduce the OBELISC dataset, an open web-scale filtered dataset of interleaved image-text documents comprising 141 million web pages extracted from Common Crawl, 353 million associated images, and 115 billion text tokens. We …","url":["https://arxiv.org/abs/2306.16527"]}
{"year":"2023","title":"Objaverse-XL: A Universe of 10M+ 3D Objects","authors":["M Deitke, R Liu, M Wallingford, H Ngo, O Michel… - arXiv preprint arXiv …, 2023"],"snippet":"… In language understanding, datasets like Common Crawl [1] have culminated in unprecedented capabilities of large language models such as GPT-4 [43], which in turn power mainstream applications like ChatGPT. The impact of large datasets is …","url":["https://arxiv.org/pdf/2307.05663"]}
{"year":"2023","title":"OHYEAH AT VLSP2022-EVJVQA CHALLENGE: A JOINTLY LANGUAGE-IMAGE MODEL FOR MULTILINGUAL VISUAL QUESTION ANSWERING","authors":["LN Dinh, H Le Ngoc, LQ Phan - Journal of Computer Science and Cybernetics, 2023"],"snippet":"… mT5 [5] is a massively multilingual pre-trained text-to-text transformer, which leverages T5 [11] to train on a new Common Crawl-based dataset with up to 101 languages. It has been proven to outperform many multilingual models in a variety of …","url":["https://vjs.ac.vn/index.php/jcc/article/download/18122/2543255286"]}
{"year":"2023","title":"Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback","authors":["VD Lai, C Van Nguyen, NT Ngo, T Nguyen… - arXiv preprint arXiv …, 2023"],"snippet":"… Table 1: List of 26 non-English languages in our Okapi framework along with language codes, numbers of first and second speakers (the “Pop.” column), data ratios in the CommonCrawl corpus, and language categories. The languages are …","url":["https://arxiv.org/pdf/2307.16039"]}
{"year":"2023","title":"On Bilingual Lexicon Induction with Large Language Models","authors":["Y Li, A Korhonen, I Vulić - arXiv preprint arXiv:2310.13995, 2023"],"snippet":"Bilingual Lexicon Induction (BLI) is a core task in multilingual NLP that still, to a large extent, relies on calculating cross-lingual word representations. Inspired by the global paradigm shift in NLP towards Large Language Models (LLMs), we examine …","url":["https://arxiv.org/pdf/2310.13995"]}
{"year":"2023","title":"On Corpora and Writing","authors":["M Chitez, A Dinca - Digital Writing Technologies in Higher Education …, 2023"],"snippet":"… For example, the filtered version of the Common Crawl Footnote 1 used for the pre-training dataset for GPT-3 (ie Generative Pre-trained Transformer 3 Footnote 2 ) consists of 410 billion tokens. This large quantity of data enables powerful quantitative analyses …","url":["https://link.springer.com/chapter/10.1007/978-3-031-36033-6_24"]}
{"year":"2023","title":"On generalization of the sense retrofitting model","authors":["YY Lee, TY Yen, HH Huang, YT Shiue, HH Chen - Natural Language Engineering, 2023"],"snippet":"With the aid of recently proposed word embedding algorithms, the study of semantic relatedness has progressed rapidly. However, word-level representations are still lacking for many natural language processing tasks. Various sense-level …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/on-generalization-of-the-sense-retrofitting-model/34C8E293327067D21168C01AFBA5E57B"]}
{"year":"2023","title":"On Hate Scaling Laws For Data-Swamps","authors":["A Birhane, V Prabhu, S Han, VN Boddeti - arXiv preprint arXiv:2306.13141, 2023"],"snippet":"… Given that both LAION-400M and LAION-2B-en are extracted from the CommonCrawl dataset, we hypothesize that during the race to expand the dataset to 2 billion samples, the dataset scraping module might have sampled from the low-quality …","url":["https://arxiv.org/pdf/2306.13141"]}
{"year":"2023","title":"On Methods of Data Standardization of German Social Media Comments","authors":["L Melnyk, L Feld - Journal of Computer-Assisted Linguistic Research, 2023"],"snippet":"This article is part of a larger project aiming at identifying discursive strategies in social media discourses revolving around the topic of gender diversity, for which roughly 350,000 comments were scraped from the comments sections below …","url":["https://polipapers.upv.es/index.php/jclr/article/download/19907/16253"]}
{"year":"2023","title":"On reading and interpreting black box deep neural networks","authors":["JE Dobson - International Journal of Digital Humanities, 2023"],"snippet":"The deep neural networks used in computer vision and in recent large language models are widely recognized as black boxes, a term that describes their complicated architectures and opaque decision-making mechanisms. This essay …","url":["https://link.springer.com/article/10.1007/s42803-023-00075-w"]}
{"year":"2023","title":"On the Benefits of Learning to Route in Mixture-of-Experts Models","authors":["N Dikkala, N Ghosh, R Meka, R Panigrahy, N Vyas… - Proceedings of the 2023 …, 2023"],"snippet":"… We study language modeling objective on the Common Crawl (mC4) dataset with T5 transformers. A first approach one could consider would be to compare neural networks where the router is learned versus networks where the router is frozen …","url":["https://aclanthology.org/2023.emnlp-main.583.pdf"]}
{"year":"2023","title":"On the Effectiveness of Log Representation for Log-based Anomaly Detection","authors":["X Wu, H Li, F Khomh"],"snippet":"Logs are an essential source of information for people to understand the running status of a software system. Due to the evolving modern software architecture and maintenance methods, more research efforts have been devoted to automated log …","url":["https://www.hengli.org/pdf/Wu2023LogRepresentation.pdf"]}
{"year":"2023","title":"On the Evolution of Knowledge Graphs: A Survey and Perspective","authors":["X Jiang, C Xu, Y Shen, X Sun, L Tang, S Wang, Z Chen… - arXiv preprint arXiv …, 2023"],"snippet":"Knowledge graphs (KGs) are structured representations of diversified knowledge. They are widely used in various intelligent applications. In this article, we provide a comprehensive survey on the evolution of various types of knowledge graphs (ie …","url":["https://arxiv.org/pdf/2310.04835"]}
{"year":"2023","title":"On the fractal patterns of language structures","authors":["LC Ribeiro, AT Bernardes, H Mello - Plos one, 2023"],"snippet":"… -profit CommonCrawl Foundation [39–41]. The data is publicly available in the Amazon cloud and were collected from many independent crawls from 2008 to 2017. As a reference of the magnitude of the raw data used by December 2017, the …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0285630"]}
{"year":"2023","title":"On the Generalization Ability of Retrieval-Enhanced Transformers","authors":["T Norlund, E Doostmohammadi, R Johansson… - arXiv preprint arXiv …, 2023"],"snippet":"Recent work on the Retrieval-Enhanced Transformer (RETRO) model has shown that off-loading memory from trainable weights to a retrieval database can significantly improve language modeling and match the performance of non-retrieval …","url":["https://arxiv.org/pdf/2302.12128"]}
{"year":"2023","title":"On the Importance of Data Representation for the Success of Text Classification","authors":["CY Cuello, V Jofre Caradonna, MJ Garciarena Ucelay… - … (CACIC)(La Rioja, 3 al 6 de …, 2023"],"snippet":"… We also used the GloVe embeddings trained with Common Crawl data which have 300 components. For both methods, the document … metrics were reached with vectors of 300 dimensions and, in the case of GloVe, using the pre-trained …","url":["http://sedici.unlp.edu.ar/bitstream/handle/10915/149536/Documento_completo.pdf?sequence=1"]}
{"year":"2023","title":"On the Ordering of Pooled Web Pages, Gold Assessments, and Bronze Assessments","authors":["T Sakai, S Tao, N Chen, Y Li, M Maistro, Z Chu, N Ferro - ACM Transactions on …, 2023"],"snippet":"The present study leverages a recent opportunity we had to create a new English web search test collection for the NTCIR-16 We Want Web (WWW-4) task, which concluded in June 2022. More specifically, through the test collection construction …","url":["https://dl.acm.org/doi/pdf/10.1145/3600227"]}
{"year":"2023","title":"On the Question of Authorship in Large Language Models (LLMs)","authors":["C Soos, L Haroutunian - NASKO, 2023"],"snippet":"… GPT-3’s gigantic scale came along with, of course, a gigantic training set, which includes English Wikipedia and BookCorpus along with the CommonCrawl dataset, which is a web crawl dataset consisting of the text from billions of web pages. Like …","url":["https://journals.lib.washington.edu/index.php/nasko/article/view/16299/13969"]}
{"year":"2023","title":"On the Reliability of Watermarks for Large Language Models","authors":["J Kirchenbauer, J Geiping, Y Wen, M Shu, K Saifullah… - arXiv preprint arXiv …, 2023"],"snippet":"… [2023], we use the Colossal Common Crawl Cleaned corpus (C4) dataset as a source of prompts for open-ended generation. For the human study, we adopt the “Long-Form Question Answering” (LFQA) dataset curated by Krishna et al. [2023] based on a …","url":["https://arxiv.org/pdf/2306.04634"]}
{"year":"2023","title":"On the Role of Morphological Information for Contextual Lemmatization","authors":["O Toporkov, R Agerri - arXiv preprint arXiv:2302.00407, 2023"],"snippet":"Lemmatization is a Natural Language Processing (NLP) task which consists of producing, from a given inflected word, its canonical form or lemma. Lemmatization is one of the basic tasks that facilitate downstream NLP applications, and is of …","url":["https://arxiv.org/pdf/2302.00407"]}
{"year":"2023","title":"On the State of German (Abstractive) Text Summarization","authors":["D Aumiller, J Fan, M Gertz - arXiv preprint arXiv:2301.07095, 2023"],"snippet":"With recent advancements in the area of Natural Language Processing, the focus is slowly shifting from a purely English-centric view towards more language-specific solutions, including German. Especially practical for businesses to analyze their …","url":["https://arxiv.org/pdf/2301.07095"]}
{"year":"2023","title":"On the use of sentiment analysis for linguistics research. Observations on sentiment polarity and the use of the progressive in Italian","authors":["L Violaa"],"snippet":"Today computational methods are used more and more in domains outside of their original conception. For example, sentiment analysis (SA)–a technique originally designed to infer general opinions from product reviews–is applied to make stock …","url":["https://2023.dhbenelux.org/wp-content/uploads/2023/05/DHB2023_paper_9150.pdf"]}
{"year":"2023","title":"On Web-based Visual Corpus Construction for Visual Document Understanding","authors":["D Kim, T Hong, M Yim, Y Kim, G Kim - International Conference on Document Analysis …, 2023"],"snippet":"… 5.1 Scale-up Using CommonCrawl Our initial goal was to handle tons of HTML data, such as CommonCrawl dataset Footnote 13 which consists of petabytes of data. … https://commoncrawl.github.io/cc-crawl-statistics/plots/crawlsize. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41682-8_19"]}
{"year":"2023","title":"On\" Scientific Debt\" in NLP: A Case for More Rigour in Language Model Pre-Training Research","authors":["MN Nityasya, HA Wibowo, AF Aji, GI Winata… - arXiv preprint arXiv …, 2023"],"snippet":"This evidence-based position paper critiques current research practices within the language model pre-training literature. Despite rapid recent progress afforded by increasingly better pre-trained language models (PLMs), current PLM research …","url":["https://arxiv.org/pdf/2306.02870"]}
{"year":"2023","title":"One Textbook Is All You Need","authors":["A Sawyer, I Moradi, L Welch, J Zhao, S Huang… - 2023"],"snippet":"Large Language Models don’t have a strong understanding of under-represented languages due to the lack of requisite training data [12]. Previous efforts increased model performance on low-resource languages by using news [15], synthetic data [2] …","url":["https://lucaswelch.me/images/Modulus%20Magnus%20Linguae.pdf"]}
{"year":"2023","title":"One True Pairing: Evaluating Effective Language Pairings for Fake News Detection Employing Zero-Shot Cross-Lingual Transfer","authors":["S Kasim - Soft Computing and Its Engineering Applications: 4th …, 2023"],"snippet":"… [5] conducted unsupervised training of cross-lingual embeddings at very large scale using the CommonCrawl Corpus. To develop XLM-R, which is a transformer-based multilingual masked language model, they applied a SentencePiece model directly …","url":["https://link.springer.com/chapter/10.1007/978-3-031-27609-5_2"]}
{"year":"2023","title":"Open Government Data Corpus for Table Search","authors":["M Glass, S Bagchi, O Hassanzadeh, G Rossiello… - arXiv preprint arXiv …, 2023"],"snippet":"… Web Table Retrieval [1] uses HTML tables from Common Crawl and uses crowd sourcing and query logs to gather 60 queries. These queries are then attempted over several baseline methods and the resulting tables are pooled for relevance …","url":["https://arxiv.org/pdf/2308.13560"]}
{"year":"2023","title":"Open Problems in Applied Deep Learning","authors":["M Raissi - arXiv preprint arXiv:2301.11316, 2023"],"snippet":"This work formulates the machine learning mechanism as a bi-level optimization problem. The inner level optimization loop entails minimizing a properly chosen loss function evaluated on the training data. This is nothing but the well-studied training …","url":["https://arxiv.org/pdf/2301.11316"]}
{"year":"2023","title":"OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch","authors":["J Li, Z Tang, Y Ding, P Wang, P Guo, W You, D Qiao… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs) with billions of parameters have demonstrated outstanding performance on various natural language processing tasks. This report presents OpenBA, an open-sourced 15B bilingual asymmetric seq2seq model, to …","url":["https://arxiv.org/pdf/2309.10706"]}
{"year":"2023","title":"OpenFact at CheckThat! 2023: Head-to-Head GPT vs. BERT-A Comparative Study of Transformers Language Models for the Detection of Check-worthy","authors":["M Sawiński, K Węcel, E Księżniak, M Stróżyna… - 2023"],"snippet":"This paper presents the research findings resulting from experiments conducted as part of the Check-That! Lab Task 1B-English submission at CLEF 2023. The aim of the research was to evaluate the check-worthiness of short texts in English. Various …","url":["https://www.dei.unipd.it/~faggioli/temp/CLEF2023-proceedings/paper-040.pdf"]}
{"year":"2023","title":"OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text","authors":["K Paster, MD Santos, Z Azerbayev, J Ba - arXiv preprint arXiv:2310.06786, 2023"],"snippet":"… Due to the high variance in the quality of documents from Common Crawl, we additionally use several methods for filtering and boilerplate reduction. Throughout the creation of OpenWebMath, we iteratively refined these methods to ensure that …","url":["https://arxiv.org/pdf/2310.06786"]}
{"year":"2023","title":"Opportunities for Large Language Models and Discourse in Engineering Design","authors":["J Göpfert, JM Weinand, P Kuckertz, D Stolten - arXiv preprint arXiv:2306.09169, 2023"],"snippet":"In recent years, large language models have achieved breakthroughs on a wide range of benchmarks in natural language processing and continue to increase in performance. Recently, the advances of large language models have raised interest …","url":["https://arxiv.org/pdf/2306.09169"]}
{"year":"2023","title":"OPTIMIZATION METHODS FOR MODELING DIVERSITY IN LANGUAGE TECHNOLOGIES","authors":["S Kumar - 2023"],"snippet":"Abstract Language use varies across individuals, communities, and populations giving rise to different variations with diverging vocabularies, syntax, semantics, and pragmatics. Despite rapid improvements in natural language processing systems on …","url":["https://www.lti.cs.cmu.edu/sites/default/files/kumar%2C%20sachin%20-%20THESIS.pdf"]}
{"year":"2023","title":"Optimized Tokenization for Transcribed Error Correction","authors":["T Wullach, SE Chazan - arXiv preprint arXiv:2310.10704, 2023"],"snippet":"… 2020) data set, a variant of the Common Crawl dataset that consists of 101 languages. For each language, we randomly select a set of 20M sentences that ranges from 3 to 15 words long. We use lowercase synthetic texts, remove …","url":["https://arxiv.org/pdf/2310.10704"]}
{"year":"2023","title":"Optimizing Machine Translation for Virtual Assistants: Multi-Variant Generation with VerbNet and Conditional Beam Search","authors":["M Sowanski, A Janicki - 2023"],"snippet":"In this paper, we introduce a domain-adapted machine translation (MT) model for intelligent virtual assistants (IVA) designed to translate natural language understanding (NLU) training data sets. This work uses a constrained beam search …","url":["https://annals-csis.org/proceedings/2023/pliks/8601.pdf"]}
{"year":"2023","title":"Optimizing Match-LSTM for SQuAD v2. 0","authors":["P Nsaka, J Dong, A Lee"],"snippet":"… The word vectors utilized in our model are trained on the 840B word corpora from Common Crawl data. The dimensionality of the embedding at 300 is significantly higher that the other choices of 50, 100 and 200 it provides more contextual …","url":["https://www.researchgate.net/profile/Peter-Nsaka/publication/368662438_Optimizing_Match-LSTM_for_SQuAD_v20_Stanford_CS224N_Default_Project/links/63f3adbbb1704f343f6b1376/Optimizing-Match-LSTM-for-SQuAD-v20-Stanford-CS224N-Default-Project.pdf"]}
{"year":"2023","title":"Options Speak Louder Than Words: Strategic Negativity in Earnings Calls Prior to Option Grants","authors":["N Palacio, M Toivonen - 2023"],"snippet":"We investigate whether executive compensation affects disclosure during earnings conference calls. In particular, we hypothesize that executives who have an upcoming option grant will use overly negative language in earnings calls, intending …","url":["https://openaccess.nhh.no/nhh-xmlui/bitstream/handle/11250/3096032/masterthesis.pdf?sequence=1"]}
{"year":"2023","title":"ORGANIZATIONS AS ALGORITHMS: A NEW METAPHOR FOR ADVANCING MANAGEMENT THEORY","authors":["VL Glaser, J Sloan, J Gehman"],"snippet":"According to the ‘Point’essay, management research’s reliance on corporate data threatens to replace objective theory with profit-biased ‘corporate empiricism,’undermining the scientific and ethical integrity of the field. In this ‘Counterpoint’essay, we offer a …","url":["https://www.researchgate.net/profile/Vern-Glaser-2/publication/375863735_Organizations_as_Algorithms_A_New_Metaphor_for_Advancing_Management_Theory/links/655fb1893fa26f66f421ef08/Organizations-as-Algorithms-A-New-Metaphor-for-Advancing-Management-Theory.pdf"]}
{"year":"2023","title":"Other Applications of Comparable Corpora","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"This section concerns applications of comparable corpora beyond pure machine translation. It has been argued [ 1 , 2 ] that downstream applications such as cross-lingual document classification, information retrieval or natural language inference, apart …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_7"]}
{"year":"2023","title":"Overview of the CLEF-2023 CheckThat! lab task 2 on subjectivity in news articles","authors":["A Galassi, F Ruggeri, A Barrón-Cedeño, F Alam… - M. Aliannejadi, G. Faggioli …, 2023"],"snippet":"We describe the outcome of the 2023 edition of the CheckThat! Lab at CLEF. We focus on subjectivity (Task 2), which has been proposed for the first time. It aims at fostering the technology for the identification of subjective text fragments in news …","url":["https://www.dei.unipd.it/~faggioli/temp/CLEF2023-proceedings/paper-020.pdf"]}
{"year":"2023","title":"Overview of the NTCIR-17 FairWeb-1 Task","authors":["S Tao, N Chen, T Sakai, Z Chu, H Arai, I Soboroff… - Proceedings of the 17th …, 2023"],"snippet":"This paper provides an overview of the NTCIR-17 FairWeb-1 Task. FairWeb-1 is an English web search task which seeks more than an ad-hoc web search task. Our task considers not only document relevance but also group fairness. We designed …","url":["http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings17/pdf/ntcir/01-NTCIR17-OV-FAIRWEB-TaoS.pdf"]}
{"year":"2023","title":"Overview of the TREC 2022 NeuCLIR Track","authors":["D Lawrie, S MacAvaney, J Mayfield, P McNamee…"],"snippet":"… , and Russian, drawn from the Common Crawl news collection.The documents were obtained by the Common Crawl service between August 1, … , an alternative source of the document collection can be obtained directly from Common Crawl …","url":["https://trec.nist.gov/pubs/trec31/papers/Overview_neuclir.pdf"]}
{"year":"2023","title":"Overview of Touché 2023: Argument and Causal Retrieval","authors":["A Bondarenko, M Fröbe, J Kiesel, F Schlatt, V Barriere…"],"snippet":"The goal of Touché is to foster and support the development of technologies for argument and causal retrieval and analysis. For the fourth time, we organize the Touché lab featuring four shared tasks:(a) argument retrieval for controversial topics …","url":["https://webis.de/downloads/publications/papers/bondarenko_2023a.pdf"]}
{"year":"2023","title":"OWLER: PRELIMINARY RESULTS FOR BUILDING A COLLABORATIVE OPEN WEB CRAWLER","authors":["M Dinzinger, S Zerhoudi, M Al-Maamari, M Istaiti…"],"snippet":"… The used seed URLs are a random sample from a recent CommonCrawl (CC) dump. Note that a CC dump gives no guarantee on a fair or even distribution of URLs, so the set of seed URLs could possibly be biased in any direction. …","url":["https://ca-roll.github.io/downloads/owler.pdf"]}
{"year":"2023","title":"PaLM 2 Technical Report","authors":["R Anil, AM Dai, O Firat, M Johnson, D Lepikhin… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of …","url":["https://arxiv.org/pdf/2305.10403"]}
{"year":"2023","title":"Palmyra-Med: Instruction-Based Fine-Tuning of LLMs Enhancing Medical Domain Performance","authors":["K Kamble, W AlShikh"],"snippet":"The development of Large Language Models (LLMs) has greatly impacted natural language processing tasks by demonstrating exceptional performance across various applications. However, a significant challenge faced by these models is their …","url":["https://www.researchgate.net/profile/Waseem-Alshikh/publication/372157453_Palmyra-Med_Instruction-Based_Fine-Tuning_of_LLMs_Enhancing_Medical_Domain_Performance/links/64a6e10c8de7ed28ba7e1598/Palmyra-Med-Instruction-Based-Fine-Tuning-of-LLMs-Enhancing-Medical-Domain-Performance.pdf"]}
{"year":"2023","title":"Paloma: A Benchmark for Evaluating Language Model Fit","authors":["I Magnusson, A Bhagia, V Hofmann, L Soldaini, AH Jha… - arXiv preprint arXiv …, 2023"],"snippet":"… pretraining without data beyond Common Crawl leads to inconsistent fit to many domains. … are trained only on data derived from Common Crawl (C4, FALCON REFINEDWEB, and MC4… majority of our domains are not sourced from Common …","url":["https://arxiv.org/pdf/2312.10523"]}
{"year":"2023","title":"PALS: Personalized Active Learning for Subjective Tasks in NLP","authors":["K Kanclerz, K Karanowski, J Bielaniewicz, M Gruza… - Proceedings of the 2023 …, 2023"],"snippet":"For subjective NLP problems, such as classification of hate speech, aggression, or emotions, personalized solutions can be exploited. Then, the learned models infer about the perception of the content independently for each reader. To acquire …","url":["https://aclanthology.org/2023.emnlp-main.823.pdf"]}
{"year":"2023","title":"Panda LLM: Training Data and Evaluation for Open-Sourced Chinese Instruction-Following Large Language Models","authors":["F Jiao, B Ding, T Luo, Z Mo - arXiv preprint arXiv:2305.03025, 2023"],"snippet":"This project focuses on enhancing open-source large language models through instruction-tuning and providing comprehensive evaluations of their performance. We explore how various training data factors, such as quantity, quality, and linguistic …","url":["https://arxiv.org/pdf/2305.03025"]}
{"year":"2023","title":"PandeMedia: an annotated corpus of digital media for issue salience","authors":["DC Almeida - 2022"],"snippet":"… Though available at the start of this project, these large datasets from Common Crawl would not significantly reduce the amount of work necessary to build the pipeline, because metadata curation and data parsing are still necessary to locate …","url":["https://repositorio.ul.pt/bitstream/10451/55576/1/TM_David_Almeida.pdf"]}
{"year":"2023","title":"PanGu-{\\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing","authors":["X Ren, P Zhou, X Meng, X Huang, Y Wang, W Wang… - arXiv preprint arXiv …, 2023"],"snippet":"The scaling of large language models has greatly improved natural language understanding, generation, and reasoning. In this work, we develop a system that trained a trillion-parameter language model on a cluster of Ascend 910 AI …","url":["https://arxiv.org/pdf/2303.10845"]}
{"year":"2023","title":"PaniniQA: Enhancing Patient Education Through Interactive Question Answering","authors":["P Cai, Z Yao, F Liu, D Wang, M Reilly, H Zhou, L Li… - arXiv preprint arXiv …, 2023"],"snippet":"Patient portal allows discharged patients to access their personalized discharge instructions in electronic health records (EHRs). However, many patients have difficulty understanding or memorizing their discharge instructions. In this paper, we …","url":["https://arxiv.org/pdf/2308.03253"]}
{"year":"2023","title":"PAPERS IN ENGLISH","authors":["F Adilova, R Davronov, R Safarov - … редактор: Ахметов Сайранбек Махсутович, д-р …, 2023"],"snippet":"… Distributed word representations for 157 distinct languages were created using the Wikipedia and Common Crawl databases [8]. The author's Uzbek Wikipedia model has 110K words, but the Common Crawl model only has 830K words. They …","url":["https://api.scienceweb.uz/storage/publication_files/4164/13954/653b94725edea___10(115_6)_compressed.pdf#page=28"]}
{"year":"2023","title":"Parameter-Efficient Fine-Tuning without Introducing New Latency","authors":["B Liao, Y Meng, C Monz - arXiv preprint arXiv:2305.16742, 2023"],"snippet":"Parameter-efficient fine-tuning (PEFT) of pre-trained language models has recently demonstrated remarkable achievements, effectively matching the performance of full fine-tuning while utilizing significantly fewer trainable parameters, and consequently …","url":["https://arxiv.org/pdf/2305.16742"]}
{"year":"2023","title":"Pashto offensive language detection: a benchmark dataset and monolingual Pashto BERT","authors":["I Haq, W Qiu, J Guo, P Tang - PeerJ Computer Science, 2023"],"snippet":"… XLM-R is trained on 2.5TB of CommonCrawl data in 100 languages simultaneously. This model outperforms other multilingual models on many NLP tasks, demonstrating its effectiveness at learning cross-lingual representations. We …","url":["https://peerj.com/articles/cs-1617/"]}
{"year":"2023","title":"Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script","authors":["X Cao, D Dawa, N Qun, T Nyima"],"snippet":"The textual adversarial attack refers to an attack method in which the attacker adds imperceptible perturbations to the original texts by elaborate design so that the NLP (natural language processing) model produces false judgments. This method is also used to …","url":["https://trustnlpworkshop.github.io/papers/6.pdf"]}
{"year":"2023","title":"PDF investigation with parser differentials and ontology","authors":["D Lam, L Li, C Anderson - 2023"],"snippet":"This paper describes the Verifiable Automatic Language Analysis and Recognition for Inputs (VALARIN) system to process, evaluate, and flag unsafe PDFs. The system extracts error features from a collection of PDF parsers, and organizes the different …","url":["https://www.techrxiv.org/articles/preprint/PDF_investigation_with_parser_differentials_and_ontology/23290277/1/files/41098616.pdf"]}
{"year":"2023","title":"PDFTriage: Question Answering over Long, Structured Documents","authors":["J Saad-Falcon, J Barrow, A Siu, A Nenkova, RA Rossi… - arXiv preprint arXiv …, 2023"],"snippet":"… For our documents, we sampled 1000 documents from the common crawl to get visually-rich, professional documents from various domains, then subsampled 100 documents based on their reading level (Flesch… 3https://mturk.com 4https://commoncrawl.org/ …","url":["https://arxiv.org/pdf/2309.08872"]}
{"year":"2023","title":"PDHF: Effective Phishing Detection Model Combining Optimal Artificial and Automatic Deep Features","authors":["E Zhu, K Cheng, Z Zhang, H Wang - Computers & Security, 2023"],"snippet":"Currently, the increasing number of high-volume phishing attacks is among the largest threats to networking environments on a daily basis. During such a severe attack, researchers prefer to extract numerous features to improve the accuracy of …","url":["https://www.sciencedirect.com/science/article/pii/S0167404823004716"]}
{"year":"2023","title":"Pearls and pitfalls of ChatGPT in medical oncology","authors":["J Blum, AK Menta, X Zhao, VB Yang, MA Gouda… - Trends in Cancer, 2023"],"snippet":"… Common Crawl is an open repository of web data from billions of web pages, consisting of petabytes of information on web pages, images… medical literature, it is diluted by unverified information contained in the Common Crawl, WebText2, and …","url":["https://www.sciencedirect.com/science/article/pii/S2405803323001097"]}
{"year":"2023","title":"Performance of Generative Large Language Models on Ophthalmology Board Style Questions","authors":["LZ Cai, A Shaheen, A Jin, R Fukui, SY Jonathan… - American Journal of …, 2023"],"snippet":"… The specialized medical information used to train these LLMs is limited, as they are currently trained on publicly available datasets designed for natural language processing such as Common Crawl, WebText, Wikipedia, and available Web Books …","url":["https://www.sciencedirect.com/science/article/pii/S0002939423002301"]}
{"year":"2023","title":"PERFORMANCE STUDY OF THE TEXT ANALYSIS MODULE IN THE PROPOSED MODEL OF AUTOMATIC SPEAKER'S SPEECH ANNOTATION","authors":["О БАРКОВСЬКА - Computer systems and information technologies, 2022"],"snippet":"… This solution was trained in 101 languages on a corpus of Common Crawl web pages, and supplemented with the XL-SUM dataset (covering 45 languages, highly abstract, concise and high-end as evidenced by human and internal evaluation) …","url":["https://csitjournal.khmnu.edu.ua/index.php/csit/article/download/182/112"]}
{"year":"2023","title":"Perplexity-Driven Case Encoding Needs Augmentation for CAPITALIZATION Robustness","authors":["RJHKR Grundkiewicz, M Junczys-Dowmunt"],"snippet":"Subword segmentation methods are the predominant solution to vocab sparsity in NMT. However, they cannot currently handle capitalization well. We re-encode case to allow the perplexity-driven SPM unigram language model algorithm to learn how …","url":["http://www.afnlp.org/conferences/ijcnlp2023/proceedings/main-short/cdrom/pdf/2023.ijcnlp-short.17.pdf"]}
{"year":"2023","title":"Persian Text Sentiment Analysis Based on BERT and Neural Networks","authors":["SR Zardak, AH Rasekh, MS Bashkari - Iranian Journal of Science and Technology …, 2023"],"snippet":"Sentiment analysis and opinion mining are studies that analyze people’s opinions, feelings, experiences, and emotions through written language. This is one of the most active research fields in natural language processing and data mining, web …","url":["https://link.springer.com/article/10.1007/s40998-023-00626-5"]}
{"year":"2023","title":"Personality Traits in Large Language Models","authors":["M Safdari, G Serapio-García, C Crepy, S Fitz… - arXiv preprint arXiv …, 2023"],"snippet":"The advent of large language models (LLMs) has revolutionized natural language processing, enabling the generation of coherent and contextually relevant text. As LLMs increasingly power conversational agents, the synthesized personality …","url":["https://arxiv.org/pdf/2307.00184"]}
{"year":"2023","title":"Perspective: Large Language Models in Applied Mechanics","authors":["N Brodnik, S Carton, C Muir, S Ghosh, D Downey… - Journal of Applied …, 2023"],"snippet":"Large language models (LLMs), such as ChatGPT and PaLM, are able to perform sophisticated text comprehension and generation tasks with little or no training. Alongside their broader societal impacts, these capabilities carry great promise for …","url":["https://asmedigitalcollection.asme.org/appliedmechanics/article/doi/10.1115/1.4062773/1164084"]}
{"year":"2023","title":"Phish-armour: phishing detection using deep recurrent neural networks","authors":["P Dhanavanthini, SS Chakkravarthy - Soft Computing, 2023"],"snippet":"Phishing is an illegal cybercrime, wherein a target gets victimized for sacrificing their personal and corporate information. It is one of the most straightforward forms of cyber-attack for hackers, as well as one of the simplest for victims to fall for. It can …","url":["https://link.springer.com/article/10.1007/s00500-023-07962-y"]}
{"year":"2023","title":"PHISHING WEBSITE DETECTION TECHNIQUES: A LITERATURE SURVEY","authors":["K Subashini, V Narmatha - Journal of Data Acquisition and Processing, 2023"],"snippet":"… The names of legal sites that are likely to be used for phishing are included in Alexa and Common Crawl [26][27]. End-users submit suspicious URLs to Phish-tank and Open-Fish to assess if these websites are phishing scams [28][29]. The dataset …","url":["https://sjcjycl.cn/article/view-2023/pdf/02_3329.pdf"]}
{"year":"2023","title":"Phishing website detection using genetic algorithm-based feature selection and parameter hypertuning","authors":["ASP Silva - 2023"],"snippet":"False webpages are created by cyber attackers who seek to mislead users into revealing sensitive and personal information, from credit card details to passwords. Phishing is a class of cyber attacks that mislead users into clicking on false websites …","url":["https://run.unl.pt/bitstream/10362/152538/1/TCDMAA1276.pdf"]}
{"year":"2023","title":"Phonetically-Grounded Language Generation: The Case of Tongue Twisters","authors":["T Loakman, C Tang, C Lin - arXiv preprint arXiv:2306.03457, 2023"],"snippet":"Previous work in phonetically-grounded language generation has mainly focused on domains such as lyrics and poetry. In this paper, we present work on the generation of tongue twisters - a form of language that is required to be phonetically …","url":["https://arxiv.org/pdf/2306.03457"]}
{"year":"2023","title":"Physics language and language use in physics--What do we know and how AI might enhance language-related research and instruction","authors":["P Wulff - European Journal of Physics, 2023"],"snippet":"Abstract Language is an important resource for physicists and learners of physics to construe physical phenomena and processes, and communicate ideas. Moreover, any physics-related instructional setting is inherently language-bound, and physics …","url":["https://iopscience.iop.org/article/10.1088/1361-6404/ad0f9c/pdf"]}
{"year":"2023","title":"PLACES: Prompting Language Models for Social Conversation Synthesis","authors":["M Chen, A Papangelis, C Tao, S Kim, A Rosenbaum… - arXiv preprint arXiv …, 2023"],"snippet":"… 2020) or Common Crawl. This allows language models to have exposure to a large amount of linguistic diversity, but this also results in exposure to a lot of hateful, … a preliminary analysis of undesirable content in the common crawl corpus. arXiv …","url":["https://arxiv.org/pdf/2302.03269"]}
{"year":"2023","title":"Poisoning Web-Scale Training Datasets is Practical","authors":["N Carlini, M Jagielski, CA Choquette-Choo, D Paleka… - arXiv preprint arXiv …, 2023"],"snippet":"… For example, both Wikipedia and Common Crawl regularly produce snapshots of their entire database. This simplifies access for people … We will investigate this attack on Wikipedia-derived datasets, but also discuss how similar vulnerabilities …","url":["https://arxiv.org/pdf/2302.10149"]}
{"year":"2023","title":"Polyglot or Not? Measuring Multilingual Encyclopedic Knowledge in Foundation Models","authors":["T Schott, D Furman, S Bhat - Proceedings of the 2023 Conference on Empirical …, 2023"],"snippet":"In this work, we assess the ability of foundation models to recall encyclopedic knowledge across a wide range of linguistic contexts. To support this, we: 1) produce a 20-language dataset that contains 303k factual associations paired with …","url":["https://aclanthology.org/2023.emnlp-main.691.pdf"]}
{"year":"2023","title":"PolyLM: An Open Source Polyglot Large Language Model","authors":["X Wei, H Wei, H Lin, T Li, P Zhang, X Ren, M Li, Y Wan… - arXiv preprint arXiv …, 2023"],"snippet":"… For instance, Thai and Indonesian have over 300 million (M) speakers, yet the size of these two languages in common crawl-based dataset … and CommonCrawl web documents as the negative samples. To sum up, about 28.3% data are filtered …","url":["https://arxiv.org/pdf/2307.06018"]}
{"year":"2023","title":"PooRaa‐Agri KG: An agricultural knowledge graph‐based simplified multilingual query system","authors":["N Sivakumar, P Srinivasan, M Kannan, VP - Expert Systems"],"snippet":"The current work proposes PooRaa‐Agri KG, an agricultural knowledge graph‐based simplified multilingual query system that works in real time to provide concise answers for agriculture‐based queries. The proposed approach accommodates real‐time …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.13434"]}
{"year":"2023","title":"Popular LLMs","authors":["T Amaratunga - … Large Language Models: Learning Their Underlying …, 2023"],"snippet":"… For the training of GPT-2, the CommonCrawl corpus was initially considered because of its large size. CommonCrawl is a large text corpus created … Unlike CommonCrawl, WebText was generated by scraping only pages linked to Reddit …","url":["https://link.springer.com/chapter/10.1007/979-8-8688-0017-7_5"]}
{"year":"2023","title":"Posthuman Bodies: Why They (Still) Matter","authors":["NK Hayles - Mapping the Posthuman"],"snippet":"Emphasizing the common capacity for cognition, this chapter presents an integrated framework that includes humans, nonhuman biological lifeforms, and computational media. It clearly distinguishes between the agential powers of material processes …","url":["https://www.taylorfrancis.com/chapters/edit/10.4324/9781003322603-3/posthuman-bodies-katherine-hayles"]}
{"year":"2023","title":"Practical Named Entity Recognition: The Role of Entity and Its Context","authors":["O Agarwal - 2023"],"snippet":"Neural supervised models for named entity recognition perform well within the same domain but fail to recognize entities not seen in the (pre-) training data with high accuracy. For better generalization, it is essential that models are able to recognize …","url":["https://search.proquest.com/openview/287c19e142ec4083a741bcf00f23209b/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Pre-processing and Resource Modelling for English-Assamese NMT System","authors":["MA Ahmed, K Kashyap, SK Sarma - 2023 4th International Conference on Computing …, 2023"],"snippet":"Neural Machine Translation (NMT) modelling for low-resourced languages is usually under-explored lacking proper analysis in the pre-processing stages which could potentially influence the performance of the model. Assamese, an indigenous …","url":["https://ieeexplore.ieee.org/abstract/document/10127567/"]}
{"year":"2023","title":"Pre-Training for Manipulation: The Case for Shape Biased Vision Transformers","authors":["K Burns, T Yu, C Finn, K Hausman"],"snippet":"Inspired by the success of transfer learning in computer vision, roboticists have investigated visual pre-training as a means to learn visuallyrobust policies from pixels. To that end, past work has favored large object interaction data, such as first …","url":["https://kayburns.github.io/media/robust_manipulation_with_spatial_features.pdf"]}
{"year":"2023","title":"PrecogIIITH@ WASSA2023: Emotion Detection for Urdu-English Code-mixed Text","authors":["BH Vedula, P Kodali, M Shrivastava, P Kumaraguru"],"snippet":"Code-mixing refers to the phenomenon of using two or more languages interchangeably within a speech or discourse context. This practice is particularly prevalent on social media platforms, and determining the embedded affects in a …","url":["https://precog.iiit.ac.in/pubs/WASSA_ACL23_sharedtask_emotion_cameraready.pdf"]}
{"year":"2023","title":"Predicting COVID-19 Related Tweets Using Ensemble of Transformers Models","authors":["Q Ismail, M Massadeh, QB Baker - 2022 IEEE/ACS 19th International Conference on …, 2022"],"snippet":"… We also utilized RoBERTa in addition to BERT; RoBERTa is a powerful pre-trained linguistic model used for English; because RoBERTa was developed using 160GB of text from CommonCrawl, Wikipedia, news sources, novels, and other online …","url":["https://ieeexplore.ieee.org/abstract/document/10017516/"]}
{"year":"2023","title":"PreSTU: Pre-Training for Scene-Text Understanding (Supplementary Material)","authors":["J Kil, S Changpinyo, X Chen, H Hu, S Goodman…"],"snippet":"… Our language module is initialized from mT5-Base [33], a multilingual variant of T5 [23], pre-trained on a new Common Crawlbased dataset with 101 different languages. During training, all parameters in vision and language blocks are …","url":["https://openaccess.thecvf.com/content/ICCV2023/supplemental/Kil_PreSTU_Pre-Training_for_ICCV_2023_supplemental.pdf"]}
{"year":"2023","title":"Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy","authors":["D Ippolito, F Tramèr, M Nasr, C Zhang, M Jagielski…"],"snippet":"Studying data memorization in neural language models helps us understand the risks (eg, to privacy or copyright) associated with models regurgitating training data and aids in the development of countermeasures. Many prior works—and some …","url":["https://sigdialinlg2023.github.io/static/papers/inlg/12_Paper.pdf"]}
{"year":"2023","title":"Prevention or Promotion? Predicting Author's Regulatory Focus","authors":["A Velutharambath, K Sassenberg, R Klinger - Northern European Journal of …, 2023"],"snippet":"People differ fundamentally in what motivates them to pursue a goal and how they approach it. For instance, some people seek growth and show eagerness, whereas others prefer security and are vigilant. The concept of regulatory focus is employed …","url":["https://nejlt.ep.liu.se/article/download/4561/3982"]}
{"year":"2023","title":"Priorities for Generative AI Regulation in the UK: CREATe response to the Digital Regulation Cooperation Forum (DRCF)","authors":["M Eben, K Erickson, M Kretschmer, G Cifrodelli, Z Li… - 2023"],"snippet":"In July 2023 the UK Digital Regulation Cooperation Forum (DRCF) issued a request for comment on the status of generative AI and priority regulatory concerns. The DRCF is comprised of four of the UK’s major regulators: the Competition and …","url":["https://eprints.gla.ac.uk/306163/1/306163.pdf"]}
{"year":"2023","title":"Privacy Implications of Retrieval-Based Language Models","authors":["Y Huang, S Gupta, Z Zhong, K Li, D Chen - arXiv preprint arXiv:2305.14888, 2023"],"snippet":"Retrieval-based language models (LMs) have demonstrated improved interpretability, factuality, and adaptability compared to their parametric counterparts, by incorporating retrieved text from external datastores. While it is well known that …","url":["https://arxiv.org/pdf/2305.14888"]}
{"year":"2023","title":"Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models","authors":["AG Carranza, R Farahani, N Ponomareva, A Kurakin… - arXiv preprint arXiv …, 2023"],"snippet":"We propose a novel approach for developing privacy-preserving large-scale recommender systems using differentially private (DP) large language models (LLMs) which overcomes certain challenges and limitations in DP training these complex …","url":["https://arxiv.org/pdf/2305.05973"]}
{"year":"2023","title":"PrivacyGLUE: A Benchmark Dataset for General Language Understanding in Privacy Policies","authors":["A Shankar, A Waldis, C Bless, MA Rodriguez… - 2023"],"snippet":"Benchmarks for general language understanding have been rapidly developing in recent years of NLP research, particularly because of their utility in choosing strong-performing models for practical downstream applications. While benchmarks have been …","url":["https://www.preprints.org/manuscript/202303.0046/download/final_file"]}
{"year":"2023","title":"Private Federated Learning in Gboard","authors":["Y Zhang, D Ramage, Z Xu, Y Zhang, S Zhai, P Kairouz - arXiv preprint arXiv …, 2023"],"snippet":"… We have employed model pre-training on public C4 corpus based on Common Crawl dataset [15] combined with training configuration tuning, and achieved almost neutral utility change measured by prediction picked ratio: the ratio of picked …","url":["https://arxiv.org/pdf/2306.14793"]}
{"year":"2023","title":"Private Web Search with Tiptoe","authors":["A Henzinger, E Dauterman, H Corrigan-Gibbs… - Cryptology ePrint Archive, 2023"],"snippet":"… For text search, we search over the C4 data set, a cleaned version of the Common Crawl’s English web crawl corpus with 364M web pages [109, 110]. The Common Crawl data set is not as comprehensive as the crawls used by commercial …","url":["https://eprint.iacr.org/2023/1438.pdf"]}
{"year":"2023","title":"Probing Pre-trained Large Language Models for Narrative Coherence","authors":["R David - 2023"],"snippet":"The extend to which PTLLMs capture narrative coherence, given (coherent) sequences of text and a set of possible ending sequences, in a zero-shot, multilingual setting has not been explored yet. This research presents an extensive …","url":["https://fse.studenttheses.ub.rug.nl/31225/1/mCCS_2023_DavidRA.pdf"]}
{"year":"2023","title":"Probing Reasoning of Language Models with Inductive In-Context Learning","authors":["I Fostiropoulos, L Itti - International Joint Conference on Artificial Intelligence …, 2023"],"snippet":"… We attempt to use expressions directly to large corpus on 367 dataset like Common Crawl1 and Github repositories. Based 368 on sub-sample of our results it is computationally expensive 369 to perform exhaustive search and did not lead to …","url":["https://openreview.net/pdf?id=skvqz58ys1U"]}
{"year":"2023","title":"Probing Taxonomic and Thematic Embeddings for Taxonomic Information","authors":["F Klubička, JD Kelleher - arXiv preprint arXiv:2301.10656, 2023"],"snippet":"Modelling taxonomic and thematic relatedness is important for building AI with comprehensive natural language understanding. The goal of this paper is to learn more about how taxonomic information is structurally encoded in embeddings. To do …","url":["https://arxiv.org/pdf/2301.10656"]}
{"year":"2023","title":"Profiting from Data Commons: Theory, Evidence, and Strategy Implications","authors":["J Potts, A Torrance, D Harhoff, E von Hippel - Strategy Science, 2023"],"snippet":"We define data commons as repositories of freely-accessible, “open source” innovation-related data, information and knowledge. Data commons are and can be a significant resource for both innovating and innovation-adopting firms and …","url":["https://pubsonline.informs.org/doi/pdf/10.1287/stsc.2021.0080"]}
{"year":"2023","title":"PROMPTING TECHNIQUES FOR NATURAL LANGUAGE GENERATION IN THE MEDICAL DOMAIN","authors":["M Rossini, P Torroni, E Cabrio, S Villata"],"snippet":"… The model is pre-trained on a modified version of the data scraped by Common Crawl1, an open repository of data crawled from the web … Unfortunately, while the Common Crawl corpus has been used for various NLP applications throughout the …","url":["https://amslaurea.unibo.it/28396/1/master_thesis_rossini.pdf"]}
{"year":"2023","title":"Prosody Analysis of Audiobooks","authors":["C Pethe, Y Yin, S Skiena - arXiv preprint arXiv:2310.06930, 2023"],"snippet":"Recent advances in text-to-speech have made it possible to generate natural-sounding audio from text. However, audiobook narrations involve dramatic vocalizations and intonations by the reader, with greater reliance on emotions, dialogues, and …","url":["https://arxiv.org/pdf/2310.06930"]}
{"year":"2023","title":"Protectbot: A Chatbot to Protect Children on Gaming Platforms","authors":["A Faraz - 2022"],"snippet":"Online gaming no longer has limited access, as it has become available to a high percentage of children in recent years. Consequently, children are exposed to multifaceted threats, such as cyberbullying, grooming, and sexting. The online …","url":["https://scholarworks.rit.edu/cgi/viewcontent.cgi?article=12518&context=theses"]}
{"year":"2023","title":"ProteinChat: Towards Achieving ChatGPT-Like Functionalities on Protein 3D Structures","authors":["H Guo, M Huo, R Zhang, P Xie - 2023"],"snippet":"The study of proteins is critical in various scientific disciplines, but understanding their complex structure-function relationships remains challenging. Recent advancements in large language models (LLMs) have demonstrated their ability to …","url":["https://www.techrxiv.org/articles/preprint/ProteinChat_Towards_Achieving_ChatGPT-Like_Functionalities_on_Protein_3D_Structures/23120606/1/files/40841009.pdf"]}
{"year":"2023","title":"Provably Convergent Subgraph-wise Sampling for Fast GNN Training","authors":["J Wang, Z Shi, X Liang, S Ji, B Li, F Wu - arXiv preprint arXiv:2303.11081, 2023"],"snippet":"Subgraph-wise sampling -- a promising class of mini-batch training techniques for graph neural networks (GNNs -- is critical for real-world applications. During the message passing (MP) in GNNs, subgraph-wise sampling methods discard …","url":["https://arxiv.org/pdf/2303.11081"]}
{"year":"2023","title":"QASA: Advanced Question Answering on Scientific Articles","authors":["Y Lee, K Lee, S Park, D Hwang, J Kim, H Lee, M Lee - 2023"],"snippet":"Reasoning is the crux of intellectual thinking. While question answering (QA) tasks are prolific with various computational models and benchmark datasets, they mostly tackle factoid or shallow QA without asking deeper understanding. Dual process …","url":["https://openreview.net/pdf?id=5ud0h8OXwD"]}
{"year":"2023","title":"Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model","authors":["Q Ye, J Liu, D Chong, P Zhou, Y Hua, A Liu - arXiv preprint arXiv:2310.09089, 2023"],"snippet":"Integrating large language models (LLMs) into healthcare presents potential but faces challenges. Directly pre-training LLMs for domains like medicine is resource-heavy and sometimes unfeasible. Sole reliance on Supervised Fine-tuning (SFT) can result …","url":["https://arxiv.org/pdf/2310.09089"]}
{"year":"2023","title":"QLoRA: Efficient Finetuning of Quantized LLMs","authors":["T Dettmers, A Pagnoni, A Holtzman, L Zettlemoyer - arXiv preprint arXiv:2305.14314, 2023"],"snippet":"We present QLoRA, an efficient finetuning approach that reduces memory usage enough to finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit finetuning task performance. QLoRA backpropagates gradients through a …","url":["https://arxiv.org/pdf/2305.14314"]}
{"year":"2023","title":"QRDP: A System that Facilitates the Selection of English Materials for Translator Education","authors":["T Abekawa, R Miyata, K Kageura - International Conference on Asian Digital Libraries, 2023"],"snippet":"We are currently developing a system that facilitates teachers of translation to evaluate and select suitable document segments as materials for translator training. The system needs to satisfy several requirements. Firstly, because translation is an …","url":["https://link.springer.com/chapter/10.1007/978-981-99-8085-7_19"]}
{"year":"2023","title":"QUADRo: Dataset and Models for QUestion-Answer Database Retrieval","authors":["S Campese, I Lauriola, A Moschitti - arXiv preprint arXiv:2304.01003, 2023"],"snippet":"… (2021): given an input question, we queried a 2020 CommonCrawl snapshot1 using BM25 and we selected the 200 most relevant documents. Then, documents are split into sentences and a state-of-the-art sentence selector (Lauriola … 1https://commoncrawl.org/2020/?utm_sou …","url":["https://arxiv.org/pdf/2304.01003"]}
{"year":"2023","title":"Qualitative Research Methods for Large Language Models: Conducting Semi-Structured Interviews with ChatGPT and BARD on Computer Science Education","authors":["A Dengel, R Gehrlein, D Fernes, S Görlich, J Maurer… - Informatics, 2023"],"snippet":"… In 2020, they published GPT 3 [9], which was trained on around 570 GB of text from a filtered version of Common Crawl, a openly available crawl of the internet. For newer models such as GPT 3.5 and GPT 4 [1], which were released in early 2023 …","url":["https://www.mdpi.com/2227-9709/10/4/78"]}
{"year":"2023","title":"Quality Evaluation of Summarization Models for Patent Documents","authors":["J Ding, H Chen, S Kolapudi, L Pobbathi, H Nguyen - 2023 IEEE 23rd International …, 2023"],"snippet":"Several recently developed neural network models have shown their potential for automated text summarization. However, the evaluation results of these models on summarization of long text are fairly close in almost every major evaluation …","url":["https://ieeexplore.ieee.org/abstract/document/10366709/"]}
{"year":"2023","title":"Quality Optimization Methods in Neural Machine Translation Systems","authors":["A Nowakowski"],"snippet":"Chapter 1 introduces the research problem, motivation, structure and scope of the thesis. It provides an overview of the included papers, together with details on authors, venues, presentation type, and the contribution of the thesis author. The …","url":["https://bip.amu.edu.pl/__data/assets/pdf_file/0032/463667/Nowakowski-Artur_rozprawa-doktorska.pdf"]}
{"year":"2023","title":"Quality> Quantity: Synthetic Corpora from Foundation Models for Closed-Domain Extractive Question Answering","authors":["S Sengupta, C Heaton, S Ghosh, P Nakov, P Mitra - arXiv preprint arXiv:2310.16995, 2023"],"snippet":"Domain adaptation, the process of training a model in one domain and applying it to another, has been extensively explored in machine learning. While training a domain-specific foundation model (FM) from scratch is an option, recent methods have focused on …","url":["https://arxiv.org/pdf/2310.16995"]}
{"year":"2023","title":"Quantum Natural Language Processing: A New and Promising Way to Solve NLP Problems","authors":["Y Bouakba, H Belhadef - Artificial Intelligence: Theories and Applications: First …, 2023"],"snippet":"… It is well known that more dataset and more parameters are essential for training deep transformers from scratch such as, GPT-3 which has used 175 billion parameters, 96 attention layers, and a Common Crawl data-set that is 45 TB in size [7] …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28540-0_17"]}
{"year":"2023","title":"Querying Large Language Models with SQL","authors":["M Saeed, N De Cao, P Papotti - arXiv preprint arXiv:2304.00472, 2023"],"snippet":"… stored effectively in the parameters of the model: the CommonCrawl+ text corpus takes 45TB, while GPT-3 only 350GB. However, LLMs have their shortcomings, as we discuss next, including poor data manipulation skills, eg, they fail with numerical …","url":["https://arxiv.org/pdf/2304.00472"]}
{"year":"2023","title":"Question and Answer Generation from Text Using Transformers","authors":["C Srihari, S Sunagar, RK Kamat, KS Raghavendra… - International Symposium on …, 2023"],"snippet":"Natural language generation is one of the major tasks that comes under Natural Language Processing and, Question Generation (QG) and Question Answering (QA) are two NLP-based tasks that have found widespread application. The QA and QG …","url":["https://link.springer.com/chapter/10.1007/978-981-19-8094-7_15"]}
{"year":"2023","title":"Question Answer Generation in Bengali: Mitigating the scarcity of QA datasets in a low-resource language","authors":["MSSA Al Fayad, CMA Ehsan, AR Kamal"],"snippet":"… For fastText word embeddings, we use the pretrained word vector model for Bengali, trained on Common Crawl7 and Wikipedia. For back-translation, we use the \"csebuetnlp/banglat5_nmt_bn_en\" model checkpoint. To train our answer span …","url":["http://www.afnlp.org/conferences/ijcnlp2023/proceedings/main-long/cdrom/pdf/2023.ijcnlp-long.29.pdf"]}
{"year":"2023","title":"Question Answering Chatbots for Biomedical Research using Transformers","authors":["E Xygi, AD Andriopoulos, DA Koutsomitropoulos"],"snippet":"Professionals as well as the general public need effective help to access, understand and consume complex biomedical concepts. The existence of an interaction environment capable of automatically processing such information-thus …","url":["https://www.ceid.upatras.gr/webpages/koutsomi/pdf/icaiic2023.pdf"]}
{"year":"2023","title":"Question Answering System for Tamil Using Deep Learning","authors":["B Antony, NRR Paul - Speech and Language Technologies for Low …, 2023"],"snippet":"Tamil, a Dravidian language family member, is widely spoken in numerous Indian states. But languages like Tamil, are underrepresented on the web. Many NLP models perform worse with these languages when compared to English, the effects …","url":["https://link.springer.com/chapter/10.1007/978-3-031-33231-9_17"]}
{"year":"2023","title":"QUESTION GENERATION AGENT","authors":["A Azzi, V Cavalli-Sforza - 2023"],"snippet":"According to recent studies that highlight the impact of technology on modern students’ learning, it came to light that modern tools increase learners’ interactivity. However, there is still an absence of modern technological tools that can be helpful …","url":["http://www.aui.ma/sse-capstone-repository/pdf/spring2023/QUESTION%20GENERATION%20AGENT.pdf"]}
{"year":"2023","title":"Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities","authors":["J Bai, S Bai, S Yang, S Wang, S Tan, P Wang, J Lin… - arXiv preprint arXiv …, 2023"],"snippet":"… In order to improve the text-oriented tasks, we collect pdf and HTML format data from Common Crawl3 and generate synthetic OCR data in English and Chinese language with natural scenery background, following Kim et al. (2022). Finally, we …","url":["https://arxiv.org/pdf/2308.12966"]}
{"year":"2023","title":"Rapidgzip: Parallel Decompression and Seeking in Gzip Files Using Cache Prefetching","authors":["M Knespel, H Brunst - Proceedings of the 32nd International Symposium on …, 2023"],"snippet":"… 吀栀e multiple petabytes large Common Crawl [8] dataset is also distributed as a set of gzip-compressed 昀椀les. A pipeline for decompressing and preprocessing such data, eg, for use in machine learning context, would bene昀椀t from being …","url":["https://dl.acm.org/doi/abs/10.1145/3588195.3592992"]}
{"year":"2023","title":"RAVEN: Stateless Rapid IP Address Variation for Enterprise Networks.","authors":["L Wang, H Kim, P Mittal, J Rexford - Proc. Priv. Enhancing Technol., 2023"],"snippet":"Enterprise networks face increasing threats against the privacy of their clients. Existing enterprise services like Network Address Translation (NAT) offer limited privacy protection, at the cost of requiring per-flow state. In this paper, we introduce …","url":["https://petsymposium.org/2023/files/papers/issue3/popets-2023-0077.pdf"]}
{"year":"2023","title":"Re-examining cross-cultural similarity judgments using language statistics","authors":["KN Le, S Gao, MC Frank, A Carstensen - Proceedings of the Annual Meeting of the …, 2023"],"snippet":"… These models were trained on Common Crawl and Wikipedia using fastText and use character n-grams of length 5, and 10 negative examples. The training used a Continuous Bag of Words with position-weights and a window of size 5. From these …","url":["https://escholarship.org/content/qt2gf8p2pn/qt2gf8p2pn.pdf"]}
{"year":"2023","title":"Realistic but Non-Identifiable Synthetic User Data Generation","authors":["I Noble, I Vendrov, X Xu, D Ramachandran - 2023"],"snippet":"… Recent revolutions in Computer Vision and Natural Language Processing are often credited to the use of massive datasets such as ImageNet [1] and Common Crawl [2], which dramatically improved performance across a multitude of tasks, and …","url":["https://reclist.io/kdd2023-cup/papers/EVALRS2023_paper_1.pdf"]}
{"year":"2023","title":"Reclaiming Data Agency in the Age of Ubiquitous Machine Learning","authors":["EJ Wenger - 2023"],"snippet":"… For example, text generation models like ChatGPT are trained on datasets like Common Crawl [5], which is an open repository containing … Or at least this is the operating assumption of ML developers who create large-scale internet datasets like …","url":["https://search.proquest.com/openview/7542a8303694795501071b1917e60a98/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Reclaiming the Digital Commons: A Public Data Trust for Training Data","authors":["A Chan, H Bradley, N Rajkumar - arXiv preprint arXiv:2303.09001, 2023"],"snippet":"… The data trust could also start from existing efforts, such as the Common Crawl We emphasize that the process of scraping data should be a continual, iterative process given the continual growth in the amount of internet data [100]. The data …","url":["https://arxiv.org/pdf/2303.09001"]}
{"year":"2023","title":"Recommending Answers to Math Questions Using KL-Divergence and the Approximate XML Tree Matching Approach","authors":["S Gao - 2023"],"snippet":"… The dataset used by ChatGPT to train the language model is Common Crawl dataset that includes nearly a trillion of words. ChatGPT, which uses a large unsupervised corpus of tokens to train the language model, applies alternating …","url":["https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=10975&context=etd"]}
{"year":"2023","title":"Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models","authors":["T Ahmed, S Ghosh, C Bansal, T Zimmermann, X Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"Incident management for cloud services is a complex process involving several steps and has a huge impact on both service health and developer productivity. On-call engineers require significant amount of domain knowledge and manual effort for …","url":["https://arxiv.org/pdf/2301.03797"]}
{"year":"2023","title":"Red AI? Inconsistent Responses from GPT3. 5 Models on Political Issues in the US and China","authors":["D Zhou, Y Zhang - arXiv preprint arXiv:2312.09917, 2023"],"snippet":"The rising popularity of ChatGPT and other AI-powered large language models (LLMs) has led to increasing studies highlighting their susceptibility to mistakes and biases. However, most of these studies focus on models trained on English texts. Taking an …","url":["https://arxiv.org/pdf/2312.09917"]}
{"year":"2023","title":"ReDASPersuasion at SemEval-2023 Task 3: Persuasion Detection using Multilingual Transformers and Language Agnostic Features","authors":["FZ Qachfar, R Verma - Proceedings of the The 17th International Workshop on …, 2023"],"snippet":"This paper describes a multilingual persuasion detection system that incorporates persuasion technique attributes for a multi-label classification task. The proposed method has two advantages. First, it combines persuasion features with a sequence …","url":["https://aclanthology.org/2023.semeval-1.293.pdf"]}
{"year":"2023","title":"Regret and Hope on Transformers: An Analysis of Transformers on Regret and Hope Speech Detection Datasets","authors":["G Sidorov, F Balouchzahi, S Butt, A Gelbukh - Applied Sciences, 2023"],"snippet":"… than BERT, including additional data from CommonCrawl and the WebText dataset. The training … XLNet was trained on a large corpus of text from Wikipedia and the CommonCrawl dataset. … The model was trained on a large corpus of text …","url":["https://www.mdpi.com/2076-3417/13/6/3983"]}
{"year":"2023","title":"Regulating ChatGPT and other Large Generative AI Models","authors":["P Hacker, A Engel, M Mauer - arXiv preprint arXiv:2302.02337, 2023"],"snippet":"Large generative AI models (LGAIMs), such as ChatGPT or Stable Diffusion, are rapidly transforming the way we communicate, illustrate, and create. However, AI regulation, in the EU and beyond, has primarily focused on conventional AI models …","url":["https://arxiv.org/pdf/2302.02337"]}
{"year":"2023","title":"Reinforced UI Instruction Grounding: Towards a Generic UI Task Automation API","authors":["Z Zhang, W Xie, X Zhang, Y Lu - arXiv preprint arXiv:2310.04716, 2023"],"snippet":"… As for the experiments with desktop data, we collect about 37K UI images from Common Crawl2, an open repository of web crawl data. We follow the practices in the open repository3 of (Burns et al., 2022) to generate 0.5M image-instruction pairs …","url":["https://arxiv.org/pdf/2310.04716"]}
{"year":"2023","title":"RelBERT: Embedding Relations with Language Models","authors":["A Ushio, J Camacho-Collados, S Schockaert - arXiv preprint arXiv:2310.00299, 2023"],"snippet":"Many applications need access to background knowledge about how different concepts and entities are related. Although Knowledge Graphs (KG) and Large Language Models (LLM) can address this need to some extent, KGs are inevitably …","url":["https://arxiv.org/pdf/2310.00299"]}
{"year":"2023","title":"ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models","authors":["I Mirzadeh, K Alizadeh, S Mehta, CC Del Mundo… - arXiv preprint arXiv …, 2023"],"snippet":"… We chose RefinedWeb because it is a high-quality subset of Common Crawl, which is often used in the pretraining phase of LLMs, including Llama, Falcon, and OPT. We also use the validation split of WikiText [54] for measuring the sparsity and …","url":["https://arxiv.org/pdf/2310.04564"]}
{"year":"2023","title":"Remodelling internet infrastructure: A first look at platform governance in the era of ChatGPT","authors":["F McKelvey, R Hunt - 2023"],"snippet":"… nature and scope of OpenAI’s filtering of the Common Crawl set, rather mysterious. Common Crawl is a nonprofit organization that relies on a broad … Ostensibly, Common Crawl operates on a commons-based production model. At its launch in …","url":["https://osf.io/preprints/mediarxiv/9zqje/download"]}
{"year":"2023","title":"RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model","authors":["F Bie, Y Yang, Z Zhou, A Ghanem, M Zhang, Z Yao… - arXiv preprint arXiv …, 2023"],"snippet":"… The image-text pairs are retrieved from random web pages with Common Crawl [224] and are filtered by CLIP score to ensure image-text alignment. Beyond the textual descriptions, LAION400M also equips users with CLIP embeddings and KNN …","url":["https://arxiv.org/pdf/2309.00810"]}
{"year":"2023","title":"Report of the 1st Workshop on Generative AI and Law","authors":["AF Cooper, K Lee, J Grimmelmann, D Ippolito… - arXiv preprint arXiv …, 2023"],"snippet":"This report presents the takeaways of the inaugural Workshop on Generative AI and Law (GenLaw), held in July 2023. A cross-disciplinary group of practitioners and scholars from computer science and law convened to discuss the technical, doctrinal …","url":["https://arxiv.org/pdf/2311.06477"]}
{"year":"2023","title":"Report on the 16th Round of NII Testbeds and Community for Information Access Research (NTCIR-16)","authors":["T Yamamoto, Z Dou, N Kando, CLA Clarke, MP Kato… - ACM SIGIR Forum, 2023"],"snippet":"… Firstly, Chuweb21, a subset of the Common Crawl dataset, is introduced for this task. Chuweb21 contains 3,402,457 domains and 858,616,203 English web pages. Secondly, two types of relevance assessment are introduced: the Gold version given …","url":["https://dl.acm.org/doi/abs/10.1145/3582900.3582911"]}
{"year":"2023","title":"Requirements Classification for Smart Allocation: A Case Study in the Railway Industry","authors":["S Bashir, M Abbas, A Ferrari, M Saadatmand…"],"snippet":"Allocation of requirements to different teams is a typical preliminary task in large-scale system development projects. This critical activity is often performed manually and can benefit from automated requirements classification techniques. To date, limited …","url":["http://www.es.mdh.se/pdf_publications/6697.pdf"]}
{"year":"2023","title":"Research on The Evaluation of Token Imbalance Degree in NMT Corpus","authors":["H WANG, L YU, H WANG - ACTA ELECTONICA SINICA, 2023"],"snippet":"… 1 实验数据与参数设置 本文选择国际机器翻译大赛 WMT15 的 NewsCommentary-v10 和 Common Crawl corpus 以及 WMT21 … 其中,News-Commentary-v10 和 NewsCommentary-v16 语料库的词表规模设置为 30K,Com⁃ mon Crawl corpus语料库的词表规模设置为200K …","url":["https://www.ejournal.org.cn/EN/article/downloadArticleFile.do?attachType=PDF&id=13181"]}
{"year":"2023","title":"Research proposal content extraction using natural language processing and semi-supervised clustering: A demonstration and comparative analysis","authors":["BM Knisely, HH Pavliscsak - Scientometrics, 2023"],"snippet":"Funding institutions often solicit text-based research proposals to evaluate potential recipients. Leveraging the information contained in these documents could help institutions understand the supply of research within their domain. In this work, an …","url":["https://link.springer.com/article/10.1007/s11192-023-04689-3"]}
{"year":"2023","title":"Resolving Elliptical Compounds in German Medical Text","authors":["N Kammer, F Borchert, S Winkler, G De Melo… - The 22nd Workshop on …, 2023"],"snippet":"… mT5 closely follows the original T5 architecture, but was trained on a multilingual Common Crawl-based dataset called mC4 with 101 languages, including German. We performed some preliminary experiments with other models. These included a …","url":["https://aclanthology.org/2023.bionlp-1.26.pdf"]}
{"year":"2023","title":"Responsible Task Automation: Empowering Large Language Models as Responsible Task Automators","authors":["Z Zhang, X Zhang, W Xie, Y Lu - arXiv preprint arXiv:2306.01242, 2023"],"snippet":"The recent success of Large Language Models (LLMs) signifies an impressive stride towards artificial general intelligence. They have shown a promising prospect in automatically completing tasks upon user instructions, functioning as brain-like …","url":["https://arxiv.org/pdf/2306.01242"]}
{"year":"2023","title":"Rethinking Homework in the Age of Artificial Intelligence","authors":["H Ibrahim, R Asim, F Zaffar, T Rahwan, Y Zaki - IEEE Intelligent Systems, 2023"],"snippet":"… ChatGPT, for instance, is trained on a curated version of the common crawl dataset, built upon text available on the Internet. However, if this content is not properly cited, it could be considered a violation of copyright laws. Indeed, this has …","url":["https://ieeexplore.ieee.org/iel7/9670/10111508/10111520.pdf"]}
{"year":"2023","title":"Retrieving Webpages Using Online Discussions","authors":["K Ros, M Jin, J Levine, CX Zhai - Proceedings of the 2023 ACM SIGIR International …, 2023"],"snippet":"… query search over all training, validation, and testing splits, it could be expanded by collecting more webpages (eg, from the Common Crawl corpus [6]). … http://web.archive.org/web/ 20221002030422/https://campuswire.com/chatrooms [6] Common Crawl. 2022 …","url":["https://dl.acm.org/doi/abs/10.1145/3578337.3605139"]}
{"year":"2023","title":"RetVec: Resilient and Efficient Text Vectorizer","authors":["E Bursztein, M Zhang, O Vallis, X Jia, A Kurakin - arXiv preprint arXiv:2302.09207, 2023"],"snippet":"This paper describes RetVec, a resilient multilingual embedding scheme designed for neural-based text processing, including small-text classification and large-language models. RetVec combines a novel character encoding with an optional small model …","url":["https://arxiv.org/pdf/2302.09207"]}
{"year":"2023","title":"Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity Linking","authors":["H Dong, J Chen, Y He, Y Liu, I Horrocks - arXiv preprint arXiv:2302.07189, 2023"],"snippet":"Discovering entity mentions that are out of a Knowledge Base (KB) from texts plays a critical role in KB maintenance, but has not yet been fully explored. The current methods are mostly limited to the simple threshold-based approach and feature-based …","url":["https://arxiv.org/pdf/2302.07189"]}
{"year":"2023","title":"Revealing Media Bias in News Articles: NLP Techniques for Automated Frame Analysis","authors":["F Hamborg - 2023"],"snippet":"This open access book presents an interdisciplinary approach to reveal biases in English news articles reporting on a given political event. The approach named person-oriented framing analysis identifies the coverage’s different perspectives on …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=zi-wEAAAQBAJ&oi=fnd&pg=PR7&dq=commoncrawl&ots=gws7ZxYf_L&sig=o7ezwsVJPQVwe91PdSNmqiYoDJg"]}
{"year":"2023","title":"Review on Query focused Multi-Document Summarization (QMDS) with Comparative Analysis","authors":["P Roy, S Kundu - ACM Computing Surveys, 2023"],"snippet":"… AQUAMUSE is one of the recent question-answering datasets generated using the Google Natural Questions (NQ) dataset [98] and Common Crawl corpus [160]. The inputs are matched documents from the Common Crawl corpus, whereas the …","url":["https://dl.acm.org/doi/pdf/10.1145/3597299"]}
{"year":"2023","title":"REVIEWTAG: TAGGING AMAZON NEGATIVE PRODUCT REVIEW WITH DEEP LEARNING","authors":["P Kumari - 2023"],"snippet":"… It is trained on a massive dataset of text, Common Crawl, consisting of over 600 billion tokens from various sources, including web pages, news articles, and social media posts [31]. The model outputs 2 million word vectors, each with a …","url":["https://uhcl-ir.tdl.org/bitstream/handle/10657.1/3009/KUMARI-MASTERSTHESIS-2023.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"Revisiting and Improving Retrieval-Augmented Deep Assertion Generation","authors":["W Sun, H Li, M Yan, Y Lei, H Zhang - arXiv preprint arXiv:2309.10264, 2023"],"snippet":"Unit testing validates the correctness of the unit under test and has become an essential activity in software development process. A unit test consists of a test prefix that drives the unit under test into a particular state, and a test oracle (eg, assertion) …","url":["https://arxiv.org/pdf/2309.10264"]}
{"year":"2023","title":"Revisiting Entropy Rate Constancy in Text","authors":["V Verma, N Tomlin, D Klein - arXiv preprint arXiv:2305.12084, 2023"],"snippet":"… 3.2 Common Crawl News We include a subset of the Common Crawl News Dataset due to its chronological diversity. In particular, we run the majority of our experiments on GPT-2; because articles in the NYT … To address this concern, we …","url":["https://arxiv.org/pdf/2305.12084"]}
{"year":"2023","title":"Revisiting non-English Text Simplification: A Unified Multilingual Benchmark","authors":["MJ Ryan, T Naous, W Xu - arXiv preprint arXiv:2305.15678, 2023"],"snippet":"Recent advancements in high-quality, large-scale English resources have pushed the frontier of English Automatic Text Simplification (ATS) research. However, less work has been done on multilingual text simplification due to the lack of a diverse …","url":["https://arxiv.org/pdf/2305.15678"]}
{"year":"2023","title":"Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Processing","authors":["A Ghaddar, Y Wu, S Bagga, A Rashid, K Bibi… - Proceedings of the 2022 …, 2022"],"snippet":"There is a growing body of work in recent years to develop pre-trained language models (PLMs) for the Arabic language. This work addresses two major problems in existing Arabic PLMs that limit the progress of the Arabic NLU and NLG fields. First …","url":["https://aclanthology.org/2022.emnlp-main.205.pdf"]}
{"year":"2023","title":"Revolutionizing subjective assessments: A three-pronged comprehensive approach with NLP and deep learning","authors":["R Agrawal, H Mishra, I Kandasamy, SR Terni… - Expert Systems with …, 2024"],"snippet":"… The model also uses the CCNet dataset, extracted from a common crawl with a different filtering process than for OSCAR. The model’s performance measure was impossible for NER due to the limited availability of annotated corpora. The model’s …","url":["https://www.sciencedirect.com/science/article/pii/S095741742302972X"]}
{"year":"2023","title":"RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural Prompts","authors":["H Liu, Y Wu, S Zhai, B Yuan, N Zhang - Proceedings of the IEEE/CVF Conference on …, 2023"],"snippet":"The field of text-to-image generation has made remarkable strides in creating high-fidelity and photorealistic images. As this technology gains popularity, there is a growing concern about its potential security risks. However, there has been limited …","url":["https://openaccess.thecvf.com/content/CVPR2023/papers/Liu_RIATIG_Reliable_and_Imperceptible_Adversarial_Text-to-Image_Generation_With_Natural_Prompts_CVPR_2023_paper.pdf"]}
{"year":"2023","title":"Right to be Forgotten in the Era of Large Language Models: Implications, Challenges, and Solutions","authors":["D Zhang, P Finckenberg-Broman, T Hoang, S Pan… - arXiv preprint arXiv …, 2023"],"snippet":"… For example, Common Crawl data is 60% of the training data used in GPT-3 [3]; 50% of PaLM’s training dataset is social media conversations [4]; and OpenAI and Google have extensively used Reddit user posts in their large language models [5, 6 …","url":["https://arxiv.org/pdf/2307.03941"]}
{"year":"2023","title":"ROBBIE: Robust Bias Evaluation of Large Generative Language Models","authors":["D Esiobu, X Tan, S Hosseini, M Ung, Y Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"As generative large language models (LLMs) grow more performant and prevalent, we must develop comprehensive enough tools to measure and improve their fairness. Different prompt-based datasets can be used to measure social bias across …","url":["https://arxiv.org/pdf/2311.18140"]}
{"year":"2023","title":"RoBERTa-CoA: RoBERTa-Based Effective Finetuning Method Using Co-Attention","authors":["JH Kim, SW Park, JY Kim, J Park, SH Jung, CB Sim - IEEE Access, 2023"],"snippet":"… has improved upon BERT by adding Common CrawlNews (CC-News), open web text, and story data, applying dynamic masking with multiple masked words generated per sentence, removing NSP, and increasing the batch size from 256 to …","url":["https://ieeexplore.ieee.org/iel7/6287639/10005208/10299620.pdf"]}
{"year":"2023","title":"Robust Information Extraction From Unstructured Documents","authors":["M Namysł - 2023"],"snippet":"In computer science, robustness can be thought of as the ability of a system to handle erroneous or nonstandard input during execution. This thesis studies the robustness of the methods that extract structured information from unstructured …","url":["https://bonndoc.ulb.uni-bonn.de/xmlui/bitstream/handle/20.500.11811/10560/6921.pdf?sequence=2"]}
{"year":"2023","title":"ROZAM at SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis","authors":["M Rostamkhani, G Zamaninejad, S Eetemadi - … of the The 17th International Workshop …, 2023"],"snippet":"We build a model using large multilingual pretrained language model XLM-T for regression task and fine-tune it on the MINT (Multilingual INTmacy) analysis dataset which covers 6 languages for training and 4 languages for testing zero-shot …","url":["https://aclanthology.org/2023.semeval-1.278.pdf"]}
{"year":"2023","title":"RTQ: Rethinking Video-language Understanding Based on Image-text Model","authors":["X Wang, Y Li, T Gan, Z Zhang, J Lv, L Nie - Proceedings of the 31st ACM International …, 2023"],"snippet":"… Besides, Flamingo uses 2 billion image-text pairs and 27 million video-text pairs, while mPLUG-B uses 2 million videotext pairs and a large natural language corpus (WikiCorpus and common crawl) as the pre-training data. It is noteworthy that HiTeA [50] …","url":["https://dl.acm.org/doi/abs/10.1145/3581783.3612152"]}
{"year":"2023","title":"RuSentNE-2023: Evaluating Entity-Oriented Sentiment Analysis on Russian News Texts","authors":["A Golubev, N Rusnachenko, N Loukachevitch - arXiv preprint arXiv:2305.17679, 2023"],"snippet":"… The authors selected articles of 14 US newspapers from the Common Crawl news crawl (CC-NEWS). Mentions of named entities such as PERSON or ORG were automatically identified, and corresponding sentences were extracted. The …","url":["https://arxiv.org/pdf/2305.17679"]}
{"year":"2023","title":"s-elBat: a Semantic Interpretation Approach for Messy taBle-s","authors":["M Cremaschi, R Avogadro, D Chieregato - Semantic Web Challenge on Tabular Data …, 2022"],"snippet":"This paper describes s-elBat, a Semantic Table Interpretation approach. The approach inherits and improves the part of the techniques belonging to the MantisTable, an approach used and tested in previous editions of the SemTab …","url":["https://ceur-ws.org/Vol-3320/paper7.pdf"]}
{"year":"2023","title":"Sailing the Data Sea to Advance Research on the Sustainable Development Goals","authors":["A Spezzatti, E Kheradmand, K Gupta, M Peras… - The Ethics of Artificial …, 2023"],"snippet":"The Sustainable Development Goals (SDGs) are the framework adopted by the global community to encourage taking actions on the multiple challenges facing the world today to ensure environmental protection, health and well-being, and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21147-8_24"]}
{"year":"2023","title":"Saisiyat Is Where It Is At! Insights Into Backdoors And Debiasing Of Cross Lingual Transformers For Named Entity Recognition","authors":["RA Calix, J Ben-Joseph, N Lopatina, R Ashley… - 2022 IEEE International …, 2022"],"snippet":"… This RoBERTa XLM model was pre-trained on text from 100 languages which came from a Common crawl and had a size of around 2.5 terabytes. Not all languages in this corpus are equally represented in terms of amount of text and …","url":["https://ieeexplore.ieee.org/abstract/document/10020403/"]}
{"year":"2023","title":"Salogni at GeoLingIt: Geolocalization by Fine-tuning BERT","authors":["I Salogni - Proceedings of the Eighth Evaluation Campaign of …, 2023"],"snippet":"… In this work, the models pre-trained on a miscellaneous corpus (umberto-commoncrawl-… work the best performing ones are the 32k umberto-commoncrawl-cased-v1 and the 31k bert-base-… However it is necessary to remember that only umberto-commoncrawl-cased-v1 …","url":["https://ceur-ws.org/Vol-3473/paper17.pdf"]}
{"year":"2023","title":"SAND: Semantic Annotation of Numeric Data in Web Tables","authors":["Y Su, D Rafiei, BK Nazari - Proceedings of the 32nd ACM International …, 2023"],"snippet":"A large portion of quantitative information about entities is expressed as Web tables, and these tables often lack proper schema and annotation, which introduces challenges for the purpose of querying and analysis. In this paper, we introduce …","url":["https://dl.acm.org/doi/abs/10.1145/3583780.3615046"]}
{"year":"2023","title":"Sarcasm Detection in English and Arabic Tweets Using Transformer Models","authors":["R Lad - 2023"],"snippet":"… XLM-RoBERTa is pre-trained on 2.5TB of filtered CommonCrawl data containing text from 100 languages [6]. RoBERTa, on the other hand… , in gigabytes, between CommonCrawl and Wikipedia data across a plethora of languages. CommonCrawl …","url":["https://digitalcommons.dartmouth.edu/cgi/viewcontent.cgi?article=1019&context=cs_senior_theses"]}
{"year":"2023","title":"SC-Block: Supervised Contrastive Blocking within Entity Resolution Pipelines","authors":["A Brinkmann, R Shraga, C Bizer - arXiv preprint arXiv:2303.03132, 2023","C Bizer"],"snippet":"… In total, 502 million records describing products and 55 million records describing local businesses were extracted from the Common Crawl. Due to the shallow coverage of the Common Crawl, the extracted data only represents a fraction of the …","url":["https://2024.eswc-conferences.org/wp-content/uploads/2024/04/146640116.pdf","https://arxiv.org/pdf/2303.03132"]}
{"year":"2023","title":"Scalable 3D Captioning with Pretrained Models","authors":["T Luo, C Rockwell, H Lee, J Johnson - arXiv preprint arXiv:2306.07279, 2023"],"snippet":"We introduce Cap3D, an automatic approach for generating descriptive text for 3D objects. This approach utilizes pretrained models from image captioning, image-text alignment, and LLM to consolidate captions from multiple views of a 3D asset …","url":["https://arxiv.org/pdf/2306.07279"]}
{"year":"2023","title":"Scalable and Accurate Self-Supervised Multimodal Representation Learning Without Aligned Video and Text Data","authors":["V Lialin, S Rawls, D Chan, S Ghosh, A Rumshisky… - Proceedings of the IEEE …, 2023"],"snippet":"… Using Wikipedia, Common Crawl, and other text sources for dataset mining was essential in the recent NLP progress [17, 6]. CLIP [52] and ALIGN [27] demonstrated the importance of the scale of weakly-supervised data for images. …","url":["https://openaccess.thecvf.com/content/WACV2023W/Pretrain/papers/Lialin_Scalable_and_Accurate_Self-Supervised_Multimodal_Representation_Learning_Without_Aligned_Video_WACVW_2023_paper.pdf"]}
{"year":"2023","title":"Scalable Extraction of Training Data from (Production) Language Models","authors":["M Nasr, N Carlini, J Hayase, M Jagielski, AF Cooper… - arXiv preprint arXiv …, 2023"],"snippet":"This paper studies extractable memorization: training data that an adversary can efficiently extract by querying a machine learning model without prior knowledge of the training dataset. We show an adversary can extract gigabytes of training data …","url":["https://arxiv.org/pdf/2311.17035"]}
{"year":"2023","title":"SCALE: Scaling up the Complexity for Advanced Language Model Evaluation","authors":["V Rasiah, R Stern, V Matoshi, M Stürmer, I Chalkidis… - arXiv preprint arXiv …, 2023"],"snippet":"Recent strides in Large Language Models (LLMs) have saturated many NLP benchmarks (even professional domain-specific ones), emphasizing the need for novel, more challenging novel ones to properly assess LLM capabilities. In this …","url":["https://arxiv.org/pdf/2306.09237"]}
{"year":"2023","title":"Scaling Expert Language Models with Unsupervised Domain Discovery","authors":["S Gururangan, M Li, M Lewis, W Shi, T Althoff… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models are typically trained densely: all parameters are updated with respect to all inputs. This requires synchronization of billions of parameters across thousands of GPUs. We introduce a simple but effective method to …","url":["https://arxiv.org/pdf/2303.14177"]}
{"year":"2023","title":"Scaling Laws for Generative Mixed-Modal Language Models","authors":["A Aghajanyan, L Yu, A Conneau, WN Hsu… - arXiv preprint arXiv …, 2023"],"snippet":"… CommonCrawl). This also applies to auditory or visual modalities, which are captured with different sensors. Yet the decisions are not … (2022), and a custom image-text dataset scraped from Common Crawl. We remove all NSFW images and …","url":["https://arxiv.org/pdf/2301.03728"]}
{"year":"2023","title":"Scaling Speech Technology to 1,000+ Languages","authors":["V Pratap, A Tjandra, B Shi, P Tomasello, A Babu… - arXiv preprint arXiv …, 2023"],"snippet":"… MMS-lab compared to Common Crawl, then we add it to the subset of words we include in our study. This enables us to evaluate on 51 languages of the FLEURS corpus since not all languages are covered by MMS-lab and we also need to find …","url":["https://arxiv.org/pdf/2305.13516"]}
{"year":"2023","title":"Schema. org: How is it used?","authors":["MH Dang, A Gaignard, H Skaf-Molli, P Molli - International Semantic Web Conference …, 2023"],"snippet":"Schema.org defines a shared vocabulary for semantically annotating web pages. Due to the vast and diverse nature of the contributed annotations, it is not easy to understand the widespread use of Schema.org. In this poster, we rely on the …","url":["https://hal.science/hal-04250523/document"]}
{"year":"2023","title":"Science Fact vs Science Fiction: A ChatGPT Immunological Review Experiment Gone Awry","authors":["J Wittmann - Immunology Letters, 2023"],"snippet":"Artificial intelligence (AI) has made great progress in recent years. The latest chatbot to make a splash is ChatGPT. To see if this type of AI could also be helpful in creating an immunological review article, I put a planned review on different classes …","url":["https://www.sciencedirect.com/science/article/pii/S0165247823000536"]}
{"year":"2023","title":"SciFoodNER: Food Named Entity Recognition for Scientific Text","authors":["G Cenikj, G Petelin, BK Seljak, T Eftimov - 2022 IEEE International Conference on Big …, 2022"],"snippet":"… Apart from the data used for the pre-training of BERT model, RoBERTa is trained on data from 3 additional sources: the CommonCrawl News dataset [24], the OpenWebText corpus [25] and the Common Crawl Stories dataset [26]. BioBERT is …","url":["https://ieeexplore.ieee.org/abstract/document/10020459/"]}
{"year":"2023","title":"SciOL and MuLMS-Img: Introducing a Large-Scale Multimodal Scientific Dataset and Models for Image-Text Tasks in the Scientific Domain","authors":["T Tarsi, H Adel, JH Metzen, D Zhang, M Finco… - Proceedings of the IEEE …, 2024"],"snippet":"In scientific publications, a substantial part of the information is expressed via figures containing images and diagrams. Hence, the retrieval of relevant figures given a natural language query is an important real-world task. However, due to the lack of …","url":["https://openaccess.thecvf.com/content/WACV2024/papers/Tarsi_SciOL_and_MuLMS-Img_Introducing_a_Large-Scale_Multimodal_Scientific_Dataset_and_WACV_2024_paper.pdf"]}
{"year":"2023","title":"Scraping Data from Web Pages Using SPARQL Queries","authors":["R Burget - International Conference on Web Engineering, 2023"],"snippet":"… According to Web Data Commons statistics, structured data was available in 42% of the 33.8 million domains included in the Common Crawl corpus [3]. However, the use of structured data is growing slowly and is limited to certain domains. A large …","url":["https://link.springer.com/chapter/10.1007/978-3-031-34444-2_21"]}
{"year":"2023","title":"Scrapism: A Manifesto","authors":["S Lavigne - Critical AI, 2023"],"snippet":"Web scraping is a technique for automatically downloading and processing web content or converting online text and other media into structured data. This article describes the role that web scraping plays for web businesses and machine …","url":["https://read.dukeupress.edu/critical-ai/article/382464/Scrapism-A-Manifesto"]}
{"year":"2023","title":"SeaLLMs--Large Language Models for Southeast Asia","authors":["XP Nguyen, W Zhang, X Li, M Aljunied, Q Tan, L Cheng… - arXiv preprint arXiv …, 2023"],"snippet":"… data, we include web-based corpora such as Common Crawl2, journalistic content such as CC-News, text corpora with expertly-curated knowledge such as Wikipedia [9], and some scholarly publications. After collecting the data, we employ …","url":["https://arxiv.org/pdf/2312.00738"]}
{"year":"2023","title":"Seals_Lab at SemEval-2023 Task 12: Sentiment Analysis for Low-resource African Languages, Hausa and Igbo","authors":["N Raychawdhary, A Das, G Dozier, CD Seals - … of the The 17th International Workshop …, 2023"],"snippet":"… The pretraining data includes 2.5 TB of filtered CommonCrawl data with 100 languages. … and also This particular model was trained on Common Crawl Corpus and the BBC news website. After our initial experiments, our task of sentiment …","url":["https://aclanthology.org/2023.semeval-1.208.pdf"]}
{"year":"2023","title":"Search This Blog","authors":["H Josephson"],"snippet":"The California Effect occurs when California’s large market, its capacity to successfully regulate, its preference for stringent standards, the inability of the regulatory target to simply move beyond California’s jurisdiction, and non-divisibility …","url":["https://www.henryjos.com/p/a-california-effect-for-artificial.html"]}
{"year":"2023","title":"Searching for Needles in a Haystack: On the Role of Incidental Bilingualism in PaLM's Translation Capability","authors":["E Briakou, C Cherry, G Foster - arXiv preprint arXiv:2305.10266, 2023"],"snippet":"Large, multilingual language models exhibit surprisingly good zero- or few-shot machine translation capabilities, despite having never seen the intentionally-included translation examples provided to typical neural translation systems. We investigate …","url":["https://arxiv.org/pdf/2305.10266"]}
{"year":"2023","title":"SecureBERT and LLAMA 2 Empowered Control Area Network Intrusion Detection and Classification","authors":["X Li, H Fu - arXiv preprint arXiv:2311.12074, 2023"],"snippet":"… These models were trained on an extensive dataset comprising 2 trillion tokens sourced from various outlets such as web pages (CommonCrawl), open-source repository code (GitHub), Wikipedia content (in 20 different languages), public …","url":["https://arxiv.org/pdf/2311.12074"]}
{"year":"2023","title":"Segmentation-Free Streaming Machine Translation","authors":["J Iranzo-Sánchez, J Iranzo-Sánchez, A Giménez… - arXiv preprint arXiv …, 2023"],"snippet":"Streaming Machine Translation (MT) is the task of translating an unbounded input text stream in real-time. The traditional cascade approach, which combines an Automatic Speech Recognition (ASR) and an MT system, relies on an intermediate …","url":["https://arxiv.org/pdf/2309.14823"]}
{"year":"2023","title":"Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models","authors":["C Aguirre, K Sasse, I Cachola, M Dredze - arXiv preprint arXiv:2311.08472, 2023"],"snippet":"Recently, work in NLP has shifted to few-shot (in-context) learning, with large language models (LLMs) performing well across a range of tasks. However, while fairness evaluations have become a standard for supervised methods, little is known …","url":["https://arxiv.org/pdf/2311.08472"]}
{"year":"2023","title":"Self-Attention-Based Bi-LSTM Model for Sentiment Analysis on Tweets about Distance Learning in Higher Education.","authors":["I Lasri, A Riadsolh, M Elbelkacemi - … Journal of Emerging Technologies in Learning, 2023"],"snippet":"For limiting the COVID-19 spread, countries around the world have implemented prevention measures such as lockdowns, social distancing, and the closers of educational institutions. Therefore, most academic activities are shifted to distance …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=18630383&AN=164443579&h=bStCT4%2BxfhAJRiq6NGagbm98POmb0gC%2Bd5I7CB55%2BSW7FEV7Tt4WhFTl4ZAtVC0Ydiqxw1onkLZNHmC7sVrrLg%3D%3D&crl=c"]}
{"year":"2023","title":"Self-Deception: Reverse Penetrating the Semantic Firewall of Large Language Models","authors":["Z Wang, W Xie, K Chen, B Wang, Z Gui, E Wang - arXiv preprint arXiv:2308.11521, 2023"],"snippet":"Large language models (LLMs), such as ChatGPT, have emerged with astonishing capabilities approaching artificial general intelligence. While providing convenience for various societal needs, LLMs have also lowered the cost of generating harmful …","url":["https://arxiv.org/pdf/2308.11521"]}
{"year":"2023","title":"Self-Influence Guided Data Reweighting for Language Model Pre-training","authors":["M Thakkar, T Bolukbasi, S Ganapathy, S Vashishth… - arXiv preprint arXiv …, 2023"],"snippet":"Language Models (LMs) pre-trained with self-supervision on large text corpora have become the default starting point for developing models for various NLP tasks. Once the pre-training corpus has been assembled, all data samples in the corpus are …","url":["https://arxiv.org/pdf/2311.00913"]}
{"year":"2023","title":"Self-Supervised and Weakly-Supervised Domain-Adaptive Continual Pre-Training in Low-Resource Settings","authors":["A Alexandrov - 2023"],"snippet":"… Using this we process 3 Common Crawl dumps and extract all the available Bulgarian text from the .doc and .docx files they contain. Dump 2023-14 contains 52k documents and 75M words, dump 2022-49 contains 24k documents and 35M …","url":["https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/634894/1/Alexandrov_Anton.pdf"]}
{"year":"2023","title":"Self-supervised learning in natural language processing","authors":["D Ruiter - 2023"],"snippet":"Most natural language processing (NLP) learning algorithms require labeled data. While this is given for a select number of (mostly English) tasks, the availability of labeled data is sparse or non-existent for the vast majority of use-cases. To alleviate …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/36090/1/Dissertation_final_mitDefense.pdf"]}
{"year":"2023","title":"Self-supervised learning of multi-omics embeddings in the low-label, high-data regime","authors":["CJ Hurry, E Slade - arXiv preprint arXiv:2311.09962, 2023"],"snippet":"Contrastive, self-supervised learning (SSL) is used to train a model that predicts cancer type from miRNA, mRNA or RPPA expression data. This model, a pretrained FT-Transformer, is shown to outperform XGBoost and CatBoost, standard …","url":["https://arxiv.org/pdf/2311.09962"]}
{"year":"2023","title":"Self-training Reduces Flicker in Retranslation-based Simultaneous Translation","authors":["S Sen, R Sennrich, B Zhang, B Haddow - Proceedings of the 17th Conference of the …, 2023"],"snippet":"In simultaneous translation, the retranslation approach has the advantage of requiring no modifications to the inference engine. However, in order to reduce the undesirable flicker in the output, previous work has resorted to increasing the …","url":["https://aclanthology.org/2023.eacl-main.270.pdf"]}
{"year":"2023","title":"Semantic Information Extraction From Natural Language Using a Learning and Rule-Based Approach","authors":["V Singh - 2023"],"snippet":"Open Information Extraction (OIE) is a subset of Natural Language Processing (NLP) that constitutes the processing of natural language into structured and machinereadable data. This thesis uses data in Resource Description Framework (RDF) …","url":["https://keep.lib.asu.edu/system/files/c7/Singh_asu_0010N_23427.pdf"]}
{"year":"2023","title":"SEMANTIC TEXT ANALYSIS USING ARTIFICIAL NEURAL NETWORKS BASED ON NEURAL-LIKE ELEMENTS WITH TEMPORAL SIGNAL SUMMATION","authors":["K Alexander, S Eugeny, K Dmitry, P Dmitry - Проблемы искусственного интеллекта, 2023"],"snippet":"… • and, of course, Internet web-pages collected, for example, in the CommonCrawl database [9] containing about a petabyte of data, although of low quality. Filtered versions of this base can already be used for training language models, such as the …","url":["https://cyberleninka.ru/article/n/semantic-text-analysis-using-artificial-neural-networks-based-on-neural-like-elements-with-temporal-signal-summation"]}
{"year":"2023","title":"SemDeDup: Data-efficient learning at web-scale through semantic deduplication","authors":["A Abbas, K Tirumala, D Simig, S Ganguli, AS Morcos - arXiv preprint arXiv …, 2023"],"snippet":"Progress in machine learning has been driven in large part by massive increases in data. However, large web-scale datasets such as LAION are largely uncurated beyond searches for exact duplicates, potentially leaving much redundancy. Here …","url":["https://arxiv.org/pdf/2303.09540"]}
{"year":"2023","title":"Semi-Supervised Dimensional Media Sentiment Analysis via Exploring Sample Relationships","authors":["P Liu, W Qian, H Li, J Cao - IEEE Transactions on Computational Social Systems, 2023"],"snippet":"Dimensional sentiment analysis (DSA) aims to recognize continuous real-valued annotations in multidimensional spaces such as valence-arousal space. It can serve as a sentiment analysis that is more fine-grained than traditional polarity …","url":["https://ieeexplore.ieee.org/abstract/document/10238426/"]}
{"year":"2023","title":"Semi-supervised learning and bidirectional decoding for effective grammar correction in low-resource scenarios","authors":["Z Mahmoud, C Li, M Zappatore, A Solyman, A Alfatemi… - PeerJ Computer Science, 2023"],"snippet":"The correction of grammatical errors in natural language processing is a crucial task as it aims to enhance the accuracy and intelligibility of written language. However, developing a grammatical error correction (GEC) framework for low-resource …","url":["https://peerj.com/articles/cs-1639/"]}
{"year":"2023","title":"SentAlign: Accurate and Scalable Sentence Alignment","authors":["S Steingrímsson, H Loftsson, A Way - arXiv preprint arXiv:2311.08982, 2023"],"snippet":"We present SentAlign, an accurate sentence alignment tool designed to handle very large parallel document pairs. Given user-defined parameters, the alignment algorithm evaluates all possible alignment paths in fairly large documents of …","url":["https://arxiv.org/pdf/2311.08982"]}
{"year":"2023","title":"Sentence-Level Multimodal and Language-Agnostic Representations","authors":["PA Duquenne, H Schwenk, B Sagot - arXiv preprint arXiv:2308.11466, 2023"],"snippet":"We introduce SONAR, a new multilingual and multimodal fixed-size sentence embedding space. Our single text encoder, covering 200 languages, substantially outperforms existing sentence embeddings such as LASER3 and LabSE on the …","url":["https://arxiv.org/pdf/2308.11466"]}
{"year":"2023","title":"SENTENCES SIMILARITY DETECTION IN INDONESIAN POETRY COMPARISON USING SIAMESE MALSTM","authors":["E Anggriawan, F Farid, RF Sari"],"snippet":"… It contains 2 million common crawl words with 300 dimensions, providing 600 billion word-vectors. FastText is different from Google word embedding because it does the analysis in the sub word context by providing the n-gram character level …","url":["http://www.icicel.org/ell/contents/2023/4/el-17-04-02.pdf"]}
{"year":"2023","title":"Sentiment analysis in Portuguese tweets: an evaluation of diverse word representation models","authors":["D Vianna, F Carneiro, J Carvalho, A Plastino, A Paes - Language Resources and …, 2023"],"snippet":"During the past years, we have seen a steady increase in the number of social networks worldwide. Among them, Twitter has consolidated its position as one of the most influential social platforms, with Brazilian Portuguese speakers holding the fifth …","url":["https://link.springer.com/article/10.1007/s10579-023-09661-4"]}
{"year":"2023","title":"Sentiment analysis in Tourism: Fine-tuning BERT or sentence embeddings concatenation?","authors":["I Bouabdallaoui, F Guerouate, S Bouhaddour, C Saadi… - arXiv preprint arXiv …, 2023"],"snippet":"Undoubtedly that the Bidirectional Encoder representations from Transformers is the most powerful technique in making Natural Language Processing tasks such as Named Entity Recognition, Question & Answers or Sentiment Analysis, however, the …","url":["https://arxiv.org/pdf/2312.07797"]}
{"year":"2023","title":"Sentiment Analysis of Forest Fires on Social Media Networks Twitter Using the Long Short Term Memory (LSTM) Method","authors":["AA Aziz, W Maharani - KLIK: Kajian Ilmiah Informatika dan Komputer, 2023"],"snippet":"… This research will also build two corpus, namely the tweet corpus for the GloVe extension feature and the common crawl corpus for the FastText extension feature, to increase the model's accuracy. Classification of reviews through this process will …","url":["https://djournals.com/klik/article/download/866/563"]}
{"year":"2023","title":"Sentiment analysis on Hindi tweets during COVID‐19 pandemic","authors":["A Saroj, A Thakur, S Pal - Computational Intelligence"],"snippet":"… The CBOW model learns by predicting the current word based on its context, and it was trained on Common Crawl and Wikipedia. Fasttext has given remarkable results in the English language. Still, in a regional language like Hindi, it is found …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/coin.12622"]}
{"year":"2023","title":"Sentiment Analysis with Neural Models for Hungarian","authors":["LJ Laki, ZG Yang - Acta Polytechnica Hungarica, 2023"],"snippet":"Sentiment analysis is a powerful tool to gain insight into the emotional polarity of opinionated texts. Computerized applications can contribute to the establishment of nextgeneration models that can provide us with data of unprecedented quantity and …","url":["http://acta.uni-obuda.hu/Laki_Yang_134.pdf"]}
{"year":"2023","title":"Separating the Wheat from the Chaff with BREAD: An open-source benchmark and metrics to detect redundancy in text","authors":["I Caswell, L Wang, I Papadimitriou - arXiv preprint arXiv:2311.06440, 2023"],"snippet":"Data quality is a problem that perpetually resurfaces throughout the field of NLP, regardless of task, domain, or architecture, and remains especially severe for lower-resource languages. A typical and insidious issue, affecting both training data and model …","url":["https://arxiv.org/pdf/2311.06440"]}
{"year":"2023","title":"Sequence to Sequence Pre-Trained Model for Natural Language Processing","authors":["G Dhasmana, PK HR, G Prasad - … International Conference on Computer Science and …, 2023"],"snippet":"… Text available in wikipedia is of good quality but it is small for pre –trianed model On the other side common crawl web scrapes are massive but relatively low quality. Colossal clean crawled corpus which is called as C4 it can serve the purpose of pre …","url":["https://ieeexplore.ieee.org/abstract/document/10346822/"]}
{"year":"2023","title":"Sequence‐to‐sequence transfer transformer network for automatic flight plan generation","authors":["Y Yang, S Qian, M Zhang, K Cai - IET Intelligent Transport Systems, 2023"],"snippet":"In this work, a machine translation framework is proposed to tackle the flight plan generation in the air transport field. Diverging from the traditional human expert‐based way, a novel sequence‐to‐sequence transfer transformer network to automatic flight …","url":["https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/itr2.12478"]}
{"year":"2023","title":"Sequential Modeling Enables Scalable Learning for Large Vision Models","authors":["Y Bai, X Geng, K Mangalam, A Bar, A Yuille, T Darrell… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce a novel sequential modeling approach which enables learning a Large Vision Model (LVM) without making use of any linguistic data. To do this, we define a common format, \"visual sentences\", in which we can represent raw images …","url":["https://arxiv.org/pdf/2312.00785"]}
{"year":"2023","title":"Sequential Text-based Knowledge Update with Self-Supervised Learning for Generative Language Models","authors":["HR Sung, YJ Tang, YC Cheng, PL Chen, TY Li… - Proceedings of the 32nd …, 2023"],"snippet":"… articles from Common Crawl3 that contain the information of ⟨𝑒1,𝑒2, ..., 𝑒𝑇 ⟩. The details are described as follows. Inspired by the concept in Gholipour Ghalandari et al. [11], we first collect the news events that are listed in Wiki Current …","url":["https://dl.acm.org/doi/abs/10.1145/3583780.3615188"]}
{"year":"2023","title":"Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study","authors":["B Wang, W Ping, P Xu, L McAfee, Z Liu, M Shoeybi… - arXiv preprint arXiv …, 2023"],"snippet":"Large decoder-only language models (LMs) can be largely improved in terms of perplexity by retrieval (eg, RETRO), but its impact on text generation quality and downstream task accuracy is unclear. Thus, it is still an open question: shall we …","url":["https://arxiv.org/pdf/2304.06762"]}
{"year":"2023","title":"Shared Language: Linguistic Similarity in an Algebra Discussion Forum","authors":["MP Banawan, J Shin, T Arner, R Balyan, WL Leite… - Computers, 2023"],"snippet":"Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies …","url":["https://www.mdpi.com/2163962"]}
{"year":"2023","title":"Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning","authors":["M Xia, T Gao, Z Zeng, D Chen - arXiv preprint arXiv:2310.06694, 2023"],"snippet":"The popularity of LLaMA (Touvron et al., 2023a;b) and other recently emerged moderate-sized large language models (LLMs) highlights the potential of building smaller yet powerful LLMs. Regardless, the cost of training such models from scratch …","url":["https://arxiv.org/pdf/2310.06694"]}
{"year":"2023","title":"Short-Answer Grading for German: Addressing the Challenges","authors":["U Padó, Y Eryilmaz, L Kirschner - International Journal of Artificial Intelligence in …, 2023"],"snippet":"Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need …","url":["https://link.springer.com/article/10.1007/s40593-023-00383-w"]}
{"year":"2023","title":"Should ChatGPT and Bard Share Revenue with Their Data Providers? A New Business Model for the AI Era Advances in Artificial Intelligence and Machine Learning …","authors":["D Zhang - 2023"],"snippet":"… of data sources, including the CommonCrawl data, WebText, two internet-based books corpora, as well as English-language Wikipedia. The CommonCrawl data contains 410 billion tokens originally from billions of web pages collected by the …","url":["https://www.oajaiml.com/uploads/archivepdf/28781163.pdf"]}
{"year":"2023","title":"Should ChatGPT and Bard Share Revenue with Their Data Providers? A New Business Model for the AI Era","authors":["D Zhang - arXiv preprint arXiv:2305.02555, 2023"],"snippet":"… sources, including the CommonCrawl data, WebText, two internetbased books corpora, as well as English-language Wikipedia. The CommonCrawl data contains 410 billion tokens originally from billions of web pages collected by the …","url":["https://arxiv.org/pdf/2305.02555"]}
{"year":"2023","title":"Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models","authors":["E Ferrara - arXiv preprint arXiv:2304.03738, 2023"],"snippet":"As the capabilities of generative language models continue to advance, the implications of biases ingrained within these models have garnered increasing attention from researchers, practitioners, and the broader public. This article …","url":["https://arxiv.org/pdf/2304.03738"]}
{"year":"2023","title":"Sidlr: Slot and intent detection models for low-resource language varieties","authors":["SY Kwon, G Bhatia, EMB Nagoudi, AA Inciarte… - Tenth Workshop on NLP for …, 2023"],"snippet":"Intent detection and slot filling are two critical tasks in spoken and natural language understandingfor task-oriented dialog systems. In this work, we describe our participation in slot and intent detection for low-resource language varieties (SID4LR)(Aepli …","url":["https://aclanthology.org/2023.vardial-1.24.pdf"]}
{"year":"2023","title":"SIEVE: MULTIMODAL DATASET PRUNING USING IMAGE CAPTIONING MODELS","authors":["A Mahmoud, M Elhoushi, A Abbas, Y Yang, N Ardalani… - arXiv preprint arXiv …, 2023"],"snippet":"… To pretrain CLIP, billions of image-text pairs are collected using common crawl The raw data is highly diverse but contains many noisy image-text pairs, including low quality images, low quality alternative text (alt-text), and misaligned image-text …","url":["https://arxiv.org/pdf/2310.02110"]}
{"year":"2023","title":"SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore","authors":["S Min, S Gururangan, E Wallace, H Hajishirzi… - arXiv preprint arXiv …, 2023"],"snippet":"The legality of training language models (LMs) on copyrighted or otherwise restricted data is under intense debate. However, as we show, model performance significantly degrades if trained only on low-risk text (eg, out-of-copyright books or …","url":["https://arxiv.org/pdf/2308.04430"]}
{"year":"2023","title":"Simple LLM Prompting is State-of-the-Art for Robust and Multilingual Dialogue Evaluation","authors":["J Mendonça, P Pereira, JP Carvalho, A Lavie… - arXiv preprint arXiv …, 2023"],"snippet":"… This model is the multilingual version of RoBERTa, pretrained on CommonCrawl data containing 100 languages. We used a single Quadro RTX 6000 24GB GPU for the encoder experiments, and accessed ChatGPT (gpt-3.5-turbo) in late March using …","url":["https://arxiv.org/pdf/2308.16797"]}
{"year":"2023","title":"Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval","authors":["J Lin, D Alfonso-Hermelo, V Jeronymo, E Kamalloo… - arXiv preprint arXiv …, 2023"],"snippet":"The advent of multilingual language models has generated a resurgence of interest in cross-lingual information retrieval (CLIR), which is the task of searching documents in one language with queries from another. However, the rapid pace of …","url":["https://arxiv.org/pdf/2304.01019"]}
{"year":"2023","title":"Simulating Users in Interactive Web Table Retrieval","authors":["B Engelmann, T Breuer, P Schaer - arXiv preprint arXiv:2310.11931, 2023"],"snippet":"… Here, tables, with their context, are added from the Common Crawl dataset. Tables are thus present in different modalities, such as page titles, entities, text before/after, and the table itself. Modality relevance assessments were created by crowdsourcing. …","url":["https://arxiv.org/pdf/2310.11931"]}
{"year":"2023","title":"Sinhala Part of Speech Tagger using Deep Learning Techniques","authors":["M Sathsarani, T Thalawaththa, NK Galappaththi… - 2022 6th International …, 2022"],"snippet":"Natural Language Processing (NLP) is a sub-field of Artificial Intelligence (AI) that consists of a collection of computational methods motivated by theory for the automated classification and reflection of human languages. The foundation for …","url":["https://ieeexplore.ieee.org/abstract/document/10026395/"]}
{"year":"2023","title":"Sinhala-English Word Embedding Alignment: Introducing Datasets and Benchmark for a Low Resource Language","authors":["K Wickramasinghe, N de Silva - arXiv preprint arXiv:2311.10436, 2023"],"snippet":"Since their inception, embeddings have become a primary ingredient in many flavours of Natural Language Processing (NLP) tasks supplanting earlier types of representation. Even though multilingual embeddings have been used for the …","url":["https://arxiv.org/pdf/2311.10436"]}
{"year":"2023","title":"Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models","authors":["MF Chen, N Roberts, K Bhatia, J Wang, C Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"The quality of training data impacts the performance of pre-trained large language models (LMs). Given a fixed budget of tokens, we study how to best select data that leads to good downstream model performance across tasks. We develop a new …","url":["https://arxiv.org/pdf/2307.14430"]}
{"year":"2023","title":"Skill-Mix: a Flexible and Expandable Family of Evaluations for AI models","authors":["D Yu, S Kaur, A Gupta, J Brown-Cohen, A Goyal… - arXiv preprint arXiv …, 2023"],"snippet":"… We identified 17 skills that appeared with rather high frequency in the common crawl corpus. Omitting them from the evaluation appeared to make it much harder for most models (see Section 5.2). This second version is recommended. …","url":["https://arxiv.org/pdf/2310.17567"]}
{"year":"2023","title":"SKIM at WMT 2023 general translation task","authors":["K Kudo, T Ito, M Morishita, J Suzuki - Proceedings of the Eighth Conference on …, 2023"],"snippet":"… Monolingual Corpus We also used the following provided monolingual data: News Crawl, News Commentary, and Common Crawl. We backtranslated the monolingual sentences using a targetto-source model (ie, an initial translation model) …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.9.pdf"]}
{"year":"2023","title":"SLDT: Sequential Latent Document Transformer for Multilingual Document-based Dialogue","authors":["Z Ma, Z Liu, J Ye"],"snippet":"… XLM-R is trained with a cross-lingual masked language modeling objective on data in 100 languages from Common Crawl. To improve the pre-training data quality, pages from Common Crawl were filtered by an n-gram language model trained on …","url":["https://openreview.net/pdf?id=CZRH2wjjAt"]}
{"year":"2023","title":"Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators","authors":["M Yoo, J Song, H Lee, J Lee, N Kim, Y Kim, J Lee - arXiv preprint arXiv:2301.09813, 2023"],"snippet":"Graph convolutional networks (GCNs) are becoming increasingly popular as they can process a wide variety of data formats that prior deep neural networks cannot easily support. One key challenge in designing hardware accelerators for GCNs is …","url":["https://arxiv.org/pdf/2301.09813"]}
{"year":"2023","title":"SlimPajama-DC: Understanding Data Combinations for LLM Training","authors":["Z Shen, T Tao, L Ma, W Neiswanger, J Hestness… - arXiv preprint arXiv …, 2023"],"snippet":"… We tested different sampling strategies for different domains of our training data: (1) each token is trained only once during training, such as Commoncrawl, and (2) we perform more than one epoch for training on particular sources, such as the …","url":["https://arxiv.org/pdf/2309.10818"]}
{"year":"2023","title":"Smaller Language Models are Better Black-box Machine-Generated Text Detectors","authors":["F Mireshghallah, J Mattern, S Gao, R Shokri… - arXiv preprint arXiv …, 2023"],"snippet":"… The GPT-2 family is reportedly trained on the WebText dataset, GPT-3 is trained on a combination of the Common Crawl 1, WebText2, books and Wikipedia, and there is not any information released about the training data of ChatGPT. … 1https://commoncrawl.org …","url":["https://arxiv.org/pdf/2305.09859"]}
{"year":"2023","title":"Smart Home Notifications in Croatian Language: A Transformer-Based Approach","authors":["M Simunec, R Soic - 2023 17th International Conference on …, 2023"],"snippet":"Natural language generation is one of the essential components in achieving spoken interaction between a human user and a computer system. In this paper, we describe the process of generating notifications in Croatian language by employing …","url":["https://ieeexplore.ieee.org/abstract/document/10198978/"]}
{"year":"2023","title":"Smart Knowledge Submission System Based on Natural Language Processing (NLP) Leveraging on Language Modelling Approach","authors":["MA Idris, H Alsultan - Gas & Oil Technology Showcase and Conference, 2023"],"snippet":"… This led to the development of pre-trained systems such as BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer), which were trained with large language datasets, such as the …","url":["https://onepetro.org/SPEGOTS/proceedings-abstract/23GOTS/3-23GOTS/517915"]}
{"year":"2023","title":"Smart Subs Subtitling App for Watching Live Virtual Dome Performances","authors":["D Christopoulos, E Chatzi, G Sofianopoulos… - 2023 18th International …, 2023"],"snippet":"… from the Greek Wikipedia, (b) the europarl database which contains textual data from the European Parliament, including eleven different languages, including Greek which we used, (c) the oscar database created by language classification and …","url":["https://ieeexplore.ieee.org/abstract/document/10255166/"]}
{"year":"2023","title":"Smart Video Retrieval and Question Answering System","authors":["M Dubey, M Dashora, VK Shree, R Jayashree - 2023 International Conference for …, 2023"],"snippet":"More and more video content is being produced on daily basis and utilizing it to its fullest has never been easier. In this paper we propose a new solution for this problem as a smart video retrieval system, leveraging the progress made in …","url":["https://ieeexplore.ieee.org/abstract/document/10080460/"]}
{"year":"2023","title":"SMS Spam Classification–Simple Deep Learning Models With Higher Accuracy Using BUNOW And GloVe Word Embedding","authors":["S Giri, S Das, SB Das, S Banerjee - Journal of Applied Science and Engineering, 2023"],"snippet":"… tokens; 2014 Wikipedia dump with 1.6 billion tokens; Gigaword5 which has 4.3 billion tokens; the combination Gigaword5 and Wikipedia2014, which has 6 billion tokens; and 42 billion tokens of web data, from Common Crawl. Each corpus was …","url":["http://jase.tku.edu.tw/articles/jase-202310-26-10-0015.pdf"]}
{"year":"2023","title":"So2al-wa-Gwab: A new Arabic Question-Answering Dataset Trained on Answer Extraction Models","authors":["H Al-Omari, R Duwairi - ACM Transactions on Asian and Low-Resource …"],"snippet":"Question answering (QA) is the task of responding to questions posed by users automatically. A question-answering system is divided into three main components: question analysis, information retrieval, and answer extraction; where this paper has …","url":["https://dl.acm.org/doi/pdf/10.1145/3605550"]}
{"year":"2023","title":"Socially Aware Natural Language Processing with Commonsense Reasoning and Fairness in Intelligent Systems","authors":["S Saeedi - 2023"],"snippet":"Although Artificial Intelligence (AI) promises to deliver ever more user-friendly consumer applications, recent mishaps involving fake information and biased treatment serve as vivid reminders of the pitfalls of AI. AI can harbor latent biases …","url":["https://search.proquest.com/openview/60a820c6375a2dfacc20921b3e8cead3/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Soft Language Clustering for Multilingual Model Pre-training","authors":["J Zeng, Y Jiang, Y Yin, Y Jing, F Meng, B Lin, Y Cao… - arXiv preprint arXiv …, 2023"],"snippet":"Multilingual pre-trained language models have demonstrated impressive (zero-shot) cross-lingual transfer abilities, however, their performance is hindered when the target language has distant typology from source languages or when pre-training …","url":["https://arxiv.org/pdf/2306.07610"]}
{"year":"2023","title":"SOTAB: The WDC Schema. org Table Annotation Benchmark","authors":["K Korini, R Peeters, C Bizer - Semantic Web Challenge on Tabular Data to …, 2022"],"snippet":"Understanding the semantics of table elements is a prerequisite for many data integration and data discovery tasks. Table annotation is the task of labeling table elements with terms from a given vocabulary. This paper presents the WDC Schema …","url":["https://ceur-ws.org/Vol-3320/paper1.pdf"]}
{"year":"2023","title":"SoUnD Framework: Analyzing (So) cial Representation in (Un) structured (D) ata","authors":["M Díaz, S Dev, E Reif, R Denton, V Prabhakaran - arXiv preprint arXiv:2311.17259, 2023"],"snippet":"… We apply the framework in two toy examples using the Common Crawl web text corpus (C4) and LAION-400M. We also propose a set of … LAION-400M is a multimodal text and image dataset that features over 400 million image-text pairs …","url":["https://arxiv.org/pdf/2311.17259"]}
{"year":"2023","title":"Source Prompt: Coordinated Pre-training of Language Models on Diverse Corpora from Multiple Sources","authors":["Y Xu, D Lu, J Liang, X Wang, Y Geng, Y Xin, H Wu… - arXiv preprint arXiv …, 2023"],"snippet":"… For common crawl based corpora such as C4, their source information is largely unusable because their data is crawled from millions of web pages. Therefore, our current method is limited to the scenario where a certain number of small corpora …","url":["https://arxiv.org/pdf/2311.09732"]}
{"year":"2023","title":"Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models","authors":["Y Huang, Z Meng, F Liu, Y Su, N Collier, Y Lu - arXiv preprint arXiv:2308.16463, 2023"],"snippet":"Large language models exhibit enhanced zero-shot performance on various tasks when fine-tuned with instruction-following data. Multimodal instruction-following models extend these capabilities by integrating both text and images. However …","url":["https://arxiv.org/pdf/2308.16463"]}
{"year":"2023","title":"SPARSITY IN LARGE LANGUAGE MODELS","authors":["RS BACK"],"snippet":"… We chose RefinedWeb because it is a high-quality subset of Common Crawl, which is often used in the pretraining phase of LLMs, including Llama, Falcon, and OPT. We also use the validation split of WikiText (Merity et al., 2017) for measuring …","url":["https://openreview.net/pdf?id=osoWxY8q2E"]}
{"year":"2023","title":"Spatiotemportal and multilingual Semantic Machine Learning Analysis of Social Media Data for the recent protests in Europe–based on Twitter data–","authors":["K Tamás - 2023"],"snippet":"The perception of inherent tensions between justice and injustice (or the disproportion of good and bad) often press a group of people (or even the whole society) to seek change concerning politics and power, for example in the form of …","url":["https://pea.lib.pte.hu/bitstream/handle/pea/34845/KOVACS_disszertacio_final.pdf?sequence=1"]}
{"year":"2023","title":"Speak While You Think: Streaming Speech Synthesis During Text Generation","authors":["A Dekel, S Shechtman, R Fernandez, D Haws, Z Kons… - arXiv preprint arXiv …, 2023"],"snippet":"… We construct our training dataset based on the C4 (Common Crawl Cleaned Corpus) dataset [20], which was also used to train T5. As C4 contains 365M samples, we consider only a random fraction of the dataset containing 3M training and 130K …","url":["https://arxiv.org/pdf/2309.11210"]}
{"year":"2023","title":"Specious Sites: Tracking the Spread and Sway of Spurious News Stories at Scale","authors":["HWA Hanley, D Kumar, Z Durumeric - arXiv preprint arXiv:2308.02068, 2023"],"snippet":"… To ensure full coverage of each site’s published articles, we additionally gather the HTML pages indexed by Common Crawl [48] for each site during this same period. We emphasize that under 1% of articles were only found in the Common …","url":["https://arxiv.org/pdf/2308.02068"]}
{"year":"2023","title":"Spelling convention sensitivity in neural language models","authors":["E Nielsen, C Kirov, B Roark - arXiv preprint arXiv:2303.03457, 2023"],"snippet":"We examine whether large neural language models, trained on very large collections of varied English text, learn the potentially long-distance dependency of British versus American spelling conventions, ie, whether spelling is consistently …","url":["https://arxiv.org/pdf/2303.03457"]}
{"year":"2023","title":"Spot: A Natural Language Interface for Geospatial Searches in OSM","authors":["L Khellaf, IB Schlicht, J Bayer, R Bouwmeester, T Miraß… - arXiv preprint arXiv …, 2023"],"snippet":"Investigative journalists and fact-checkers have found OpenStreetMap (OSM) to be an invaluable resource for their work due to its extensive coverage and intricate details of various locations, which play a crucial role in investigating news scenes …","url":["https://arxiv.org/pdf/2311.08093"]}
{"year":"2023","title":"Sprinter: Speeding Up High-Fidelity Crawling of the Modern Web","authors":["A Goel, J Zhu, R Netravali, HV Madhyastha"],"snippet":"Crawling the web at scale forms the basis of many important systems: web search engines, smart assistants, generative AI, web archives, and so on. Yet, the research community has paid little attention to this workload in the last decade. In this paper …","url":["https://goelayu.github.io/files/sprinter-2024.pdf"]}
{"year":"2023","title":"SRBerta-BERT transformer language model for Serbian legal texts","authors":["M Bogdanovic, J Tošic"],"snippet":"… OSCAR is a large set of open data created using linguistic classification over data from the Common Crawl corpus [3]. The dataset we used consisted of 645,747 texts. The evaluation of the SRBert network was performed using 10of which consists of …","url":["https://imi.pmf.kg.ac.rs/aaa2023/pdf/accepted-finished/d93c7914a7bfff76e6c64d160e9f1281_10_05162023_084339/MilosBogdanovic-Abstract.pdf"]}
{"year":"2023","title":"SSL-GAN-RoBERTa: A robust semi-supervised model for detecting Anti-Asian COVID-19 hate speech on social media","authors":["X Su, Y Li, P Branco, D Inkpen - Natural Language Engineering, 2023"],"snippet":"Anti-Asian speech during the COVID-19 pandemic has been a serious problem with severe consequences. A hate speech wave swept social media platforms. The timely detection of Anti-Asian COVID-19-related hate speech is of utmost importance …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/D24DDC58F7DEE72216EB04196A4BB440/S1351324923000396a.pdf/div-class-title-ssl-gan-roberta-a-robust-semi-supervised-model-for-detecting-anti-asian-covid-19-hate-speech-on-social-media-div.pdf"]}
{"year":"2023","title":"Stable Bias: Analyzing Societal Representations in Diffusion Models","authors":["AS Luccioni, C Akiki, M Mitchell, Y Jernite - arXiv preprint arXiv:2303.11408, 2023"],"snippet":"As machine learning-enabled Text-to-Image (TTI) systems are becoming increasingly prevalent and seeing growing adoption as commercial services, characterizing the social biases they exhibit is a necessary first step to lowering their …","url":["https://arxiv.org/pdf/2303.11408"]}
{"year":"2023","title":"StarCoder: may the source be with you!","authors":["R Li, LB Allal, Y Zi, N Muennighoff, D Kocetkov, C Mou… - arXiv preprint arXiv …, 2023"],"snippet":"The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context …","url":["https://arxiv.org/pdf/2305.06161"]}
{"year":"2023","title":"stopes-Modular Machine Translation Pipelines","authors":["P Andrews, G Wenzek, K Heffernan, O Çelebi, A Sun… - Proceedings of the The …, 2022"],"snippet":"Neural machine translation, as other natural language deep learning applications, is hungry for data. As research evolves, the data pipelines supporting that research evolve too, oftentimes re-implementing the same core components. Despite the …","url":["https://aclanthology.org/2022.emnlp-demos.26.pdf"]}
{"year":"2023","title":"Strengthening Small and Medium-Sized Businesses' Cybersecurity: A Machine Learning-based Phishing Classification Model","authors":["SC Song - 2023"],"snippet":"… The study used 5,000 URLs from the PhishTank, OpenPhish, Alexa, and Common Crawl archives. The best model used a Random Forest algorithm and had an … The phishing URLs were extracted from phishtank.org while the legitimate …","url":["https://search.proquest.com/openview/3205e8ac8b6f3c1e6a2a02a6c2110253/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"STRESS TEST FOR BERT AND DEEP MODELS: PREDICTING WORDS FROM ITALIAN POETRY","authors":["R Delmonte, N Busetto"],"snippet":"In this paper we present a set of experiments carried out with BERT on a number of Italian sentences taken from poetry domain. The experiments are organized on the hypothesis of a very high level of difficulty in predictability at the three levels of …","url":["https://www.researchgate.net/profile/Rodolfo-Delmonte/publication/366733361_STRESS_TEST_FOR_BERT_AND_DEEP_MODELS_PREDICTING_WORDS_FROM_ITALIAN_POETRY/links/63b07957c3c99660ebbaf13a/STRESS-TEST-FOR-BERT-AND-DEEP-MODELS-PREDICTING-WORDS-FROM-ITALIAN-POETRY.pdf"]}
{"year":"2023","title":"string2string: A Modern Python Library for String-to-String Algorithms","authors":["M Suzgun, SM Shieber, D Jurafsky - arXiv preprint arXiv:2304.14395, 2023"],"snippet":"We introduce string2string, an open-source library that offers a comprehensive suite of efficient algorithms for a broad range of string-to-string problems. It includes traditional algorithmic solutions as well as recent advanced neural approaches to …","url":["https://arxiv.org/pdf/2304.14395"]}
{"year":"2023","title":"Strong Prediction: Language model surprisal explains multiple N400 effects","authors":["JA Michaelov, MD Bardolph, CK Van Petten…"],"snippet":"Theoretical accounts of the N400 are divided as to whether the amplitude of the N400 response to a stimulus reflects the extent to which the stimulus was predicted, the extent to which the stimulus is semantically similar to its preceding context, or …","url":["https://pages.ucsd.edu/~bkbergen/papers/michaelov_et_al_NoL.pdf"]}
{"year":"2023","title":"Structural Self-Supervised Objectives for Transformers","authors":["L Di Liello - arXiv preprint arXiv:2309.08272, 2023"],"snippet":"This thesis focuses on improving the pre-training of natural language models using unsupervised raw data to make them more efficient and aligned with downstream applications. In the first part, we introduce three alternative pre-training objectives to …","url":["https://arxiv.org/pdf/2309.08272"]}
{"year":"2023","title":"Students' perceptions of using ChatGPT in a physics class as a virtual tutor","authors":["L Ding, T Li, S Jiang, A Gapud - International Journal of Educational Technology in …, 2023"],"snippet":"The latest development of Generative Artificial Intelligence (GenAI), particularly ChatGPT, has drawn the attention of educational researchers and practitioners. We have witnessed many innovative uses of ChatGPT in STEM classrooms. However …","url":["https://link.springer.com/article/10.1186/s41239-023-00434-1"]}
{"year":"2023","title":"Study of ChatGPT and its Comparison with Other Mainstream Large Language Models","authors":["C Yuyang"],"snippet":"… T5 was pre-trained on 34B tokens, which filtered the publicly crawled web dataset Common Crawl to remove some duplicates, low-quality, code-looking texts, etc., and finally kept only English texts to obtain dataset C4: the Colossal Clean Crawled …","url":["http://www.ijklp.org/archives/vol13no2/Study%20of%20ChatGPT%20and%20its%20Comparison%20with%20Other%20Mainstream%20Large%20Language%20Models.pdf"]}
{"year":"2023","title":"Sub-Standards and Mal-Practices: Misinformation's Role in Insular, Polarized, and Toxic Interactions","authors":["HWA HANLEY, Z DURUMERIC"],"snippet":"… pages that were indexed by Common Crawl before August 2021. For each HTML page indexed by Common Crawl, we parse the HTML … Altogether we gather the available Common Crawl pages and scrape the HTML for 541 misinformation and …","url":["https://www.hanshanley.com/files/Sub_Standards_and_Mal_Practices.pdf"]}
{"year":"2023","title":"Subject-verb Agreement with Seq2Seq Transformers: Bigger Is Better, but Still Not Best","authors":["MA Wilson, Z Zhou, R Frank - Proceedings of the Society for Computation in …, 2023"],"snippet":"Past work (Linzen et al., 2016; Goldberg, 2019, ao) has used the performance of neural network language models on subject-verb agreement to argue that such models possess structure-sensitive grammatical knowledge. We investigate what …","url":["https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1303&context=scil"]}
{"year":"2023","title":"Submission of USTC's system for the IWSLT 2023-Offline Speech Translation Track","authors":["X Zhou, J Cui, Z Ye, Y Wang, L Xu, H Zhang, W Zhang… - Proceedings of the 20th …, 2023"],"snippet":"This paper describes the submissions of the research group USTC-NELSLIP to the 2023 IWSLT Offline Speech Translation competition, which involves translating spoken English into written Chinese. We utilize both cascaded models and end-to-end …","url":["https://aclanthology.org/2023.iwslt-1.15.pdf"]}
{"year":"2023","title":"Subversion of the Human Aura: A Crisis in Representation","authors":["NK Hayles - American Literature, 2023"],"snippet":"The human aura is now being subverted by a variety of simulacra. OpenAI’s language-generation program GPT-3 illustrates the challenges of interpreting algorithmic-generated texts. This article advocates interpretive strategies that …","url":["https://read.dukeupress.edu/american-literature/article-abstract/doi/10.1215/00029831-10575063/344236"]}
{"year":"2023","title":"Subword-Based Neural Machine Translation for Low-Resource Fusion Languages","authors":["A Nürnberger, EW De Luca, M Gasser","AM Gezmu - 2023"],"snippet":"Neural approaches, which are currently state-of-the-art in many areas, have contributed significantly to the exciting advancements in machine translation. However, Neural Machine Translation (NMT) requires a substantial quantity and …","url":["https://opendata.uni-halle.de/bitstream/1981185920/105783/1/Gezmu_Andargachew_Mekonnen_Dissertation_2023.pdf","https://repo.bibliothek.uni-halle.de/bitstream/1981185920/105783/1/Gezmu_Andargachew_Mekonnen_Dissertation_2023.pdf"]}
{"year":"2023","title":"Suicidal Text Detection in Social Media","authors":["MP Karthikeyan, I Ajay, R Magesh, G Saran - 2023"],"snippet":"This system is developed with the aim of providing and insight information of people who are personally disturbed by the factors of either their personal life or family background or bully at school or work pressure. With the help of people’s online …","url":["https://www.ijrar.org/papers/IJRAR23B1004.pdf"]}
{"year":"2023","title":"Suicide risk assessment using word-level model with dictionary-based risky posts selection","authors":["YS Tsai, ALP Chen - Multimedia Tools and Applications, 2023"],"snippet":"Suicide is a serious issue around the world and is a leading cause of death in US. In the past 20 years, the suicide rate has seen a significant increase of 35%. With the rapid development of information technology, more and more people begin to use …","url":["https://link.springer.com/article/10.1007/s11042-023-16361-2"]}
{"year":"2023","title":"SuperDialseg: A Large-scale Dataset for Supervised Dialogue Segmentation","authors":["J Jiang, C Dong, A Aizawa, S Kurohashi - arXiv preprint arXiv:2305.08371, 2023"],"snippet":"… For TextTiling+Glove, we used the version pretrained with 42 billion tokens of web data from Common Crawl.For GreedySeg and CSM, we corrected some inconsistencies in their open-sourced codes with respect to their original published …","url":["https://arxiv.org/pdf/2305.08371"]}
{"year":"2023","title":"Superlim: A Swedish Language Understanding Evaluation Benchmark","authors":["A Berdičevskis, G Bouma, R Kurtz, F Morger, J Öhman… - Proceedings of the 2023 …, 2023"],"snippet":"We present Superlim, a multi-task NLP benchmark and analysis platform for evaluating Swedish language models, a counterpart to the English-language (Super) GLUE suite. We describe the dataset, the tasks, the leaderboard and report the …","url":["https://aclanthology.org/2023.emnlp-main.506.pdf"]}
{"year":"2023","title":"Supervised Feature Selection to Improve the Accuracy for Malware Detection","authors":["D Smith, S Khorsandroo, K Roy - 2023"],"snippet":"Malware is becoming increasingly sophisticated and difficult to detect with traditional monitoring tools and antivirus software. As a result, machine learning has become a popular approach for classifying and detecting malware-related data. In this study …","url":["https://www.researchsquare.com/article/rs-2898970/latest.pdf"]}
{"year":"2023","title":"Supervised Feature-based Classification Approach to Bilingual Lexicon Induction from Specialised Comparable Corpora","authors":["AR Terryn"],"snippet":"This study, submitted to the BUCC2023 shared task on bilingual term alignment in comparable specialised corpora, introduces a supervised, feature-based classification approach. The approach employs both static cross-lingual …","url":["https://www.researchgate.net/profile/Ayla_Rigouts_Terryn2/publication/373823779_Supervised_Feature-based_Classification_Approach_to_Bilingual_Lexicon_Induction_from_Specialised_Comparable_Corpora/links/64febb3c68ca5847e3cdcbd2/Supervised-Feature-based-Classification-Approach-to-Bilingual-Lexicon-Induction-from-Specialised-Comparable-Corpora.pdf"]}
{"year":"2023","title":"Supervised Knowledge Makes Large Language Models Better In-context Learners","authors":["L Yang, S Zhang, Z Yu, G Bao, Y Wang, J Wang, R Xu… - arXiv preprint arXiv …, 2023"],"snippet":"Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the …","url":["https://arxiv.org/pdf/2312.15918"]}
{"year":"2023","title":"Supervised Machine Generated Text Detection Using LLM Encoders In Various Data Resource Scenarios","authors":["M Capobianco"],"snippet":"With the recent innovation in Large Language Models, the world has been taken by storm by the vast implications and applications of including these effective new creations into our everyday lives. However, as with most things, these new …","url":["https://digital.wpi.edu/downloads/hh63t0231"]}
{"year":"2023","title":"Support of Sparse Tensor Computing for MLIR HLS","authors":["GM Liang, CL Lee, R Lai, JK Lee - Proceedings of the 52nd International Conference …, 2023"],"snippet":"Nowadays, sparse tensor computations are widely used in machine learning. Without the multiplications in zero values, sparse tensor computation can significantly reduce the latency and power consumption. Famous frameworks like …","url":["https://dl.acm.org/doi/abs/10.1145/3605731.3605908"]}
{"year":"2023","title":"Supporting Account-Based Queries for Archived Instagram Posts","authors":["HR Jayanetti - 2023"],"snippet":"Social media has become one of the primary modes of communication in recent times, with popular platforms such as Facebook, Twitter, and Instagram leading the way. Despite its popularity, Instagram has not received as much attention in …","url":["https://search.proquest.com/openview/69156b126b64d5b62da188c26e82268f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Surface-Based Retrieval Reduces Perplexity of Retrieval-Augmented Language Models","authors":["E Doostmohammadi, T Norlund, M Kuhlmann… - arXiv preprint arXiv …, 2023"],"snippet":"Augmenting language models with a retrieval mechanism has been shown to significantly improve their performance while keeping the number of parameters low. Retrieval-augmented models commonly rely on a semantic retrieval mechanism …","url":["https://arxiv.org/pdf/2305.16243"]}
{"year":"2023","title":"Surgicberta: a pre-trained language model for procedural surgical language","authors":["M Bombieri, M Rospocher, SP Ponzetto, P Fiorini - International Journal of Data …, 2023"],"snippet":"… of the CommonCrawl News, from OpenWebText, and some stories from CommonCrawl data. RoBERTa has been trained via MLM with dynamic masking: ie, each time a sequence is input to the model, a new masking pattern is created …","url":["https://link.springer.com/article/10.1007/s41060-023-00433-5"]}
{"year":"2023","title":"SurreyAI 2023 Submission for the Quality Estimation Shared Task","authors":["A Sindhujan, D Kanojia, C Orasan, T Ranasinghe - Proceedings of the Eigth …, 2023"],"snippet":"Quality Estimation (QE) systems are important in situations where it is necessary to assess the quality of translations, but there is no reference available. This paper describes the approach adopted by the SurreyAI team for addressing the Sentence-Level …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.74.pdf"]}
{"year":"2023","title":"Survey On Machine Learning Paradigms For Phishing Website Detection","authors":["M Baduwal, P Madai, T Alam, Q Yuan"],"snippet":"Phishing attacks continue to be a major security threat for individuals and organizations alike. It causes billions of dollars in losses annually. Machine learning (ML) has shown great promise in detecting such attacks by identifying patterns and …","url":["https://www.researchgate.net/profile/Madan-Baduwal-2/publication/370658818_Survey_On_Machine_Learning_Paradigms_For_Phishing_Website_Detection/links/645c91fcf43b8a29ba42daba/Survey-On-Machine-Learning-Paradigms-For-Phishing-Website-Detection.pdf"]}
{"year":"2023","title":"Survey Paper: Automatic Title Generation for Text with RNN and Pre-trained Transformer Language Model","authors":["V Lodhwal, G Choudhary"],"snippet":"Nowadays huge amounts of text data are available due to the evolution of the Internet. Although search engines are used to select text data, it is unfeasible to go through the entire search results of text that are related to search intent. Therefore …","url":["https://www.researchgate.net/profile/Vishal-Lodhwal-2/publication/369741619_Survey_Paper_Automatic_Title_Generation_for_Text_with_RNN_and_Pre-trained_Transformer_Language_Model/links/642fd66e20f25554da158ea3/Survey-Paper-Automatic-Title-Generation-for-Text-with-RNN-and-Pre-trained-Transformer-Language-Model.pdf"]}
{"year":"2023","title":"Syntactic-Semantic Similarity Based on Dependency Tree Kernel","authors":["M Alian, A Awajan - Arabian Journal for Science and Engineering, 2023"],"snippet":"The representation of words in the vector space generated using the Word2Vec model does not capture the syntactic similarity between sentences, but only the semantic similarity by considering the context of words. To address this problem, we …","url":["https://link.springer.com/article/10.1007/s13369-023-07694-z"]}
{"year":"2023","title":"Synthetic Cross-language Information Retrieval Training Data","authors":["J Mayfield, E Yang, D Lawrie, S Barham, O Weller… - arXiv preprint arXiv …, 2023"],"snippet":"… Documents in NeuCLIR 1 are news articles extracted from Common Crawl News. The HC3 dataset consists of Chinese and Persian Tweet reply … criterion used for the NeuCLIR 1 was dropped since Twitter conversations are less coherent than …","url":["https://arxiv.org/pdf/2305.00331"]}
{"year":"2023","title":"System for Enhancing Accuracy of Noisy Text using Deep Network Language Models","authors":["R Rohit, SA Gandheesh, KS Suriya, PB Pati - 2023 IEEE 8th International Conference …, 2023"],"snippet":"… C4 dataset is a collection of English language text sourced from an open-source Common Crawl web scrape. Each record consists of an input erroneous test along with its target text. While the dataset contains many millions of sentences, for this …","url":["https://ieeexplore.ieee.org/abstract/document/10126194/"]}
{"year":"2023","title":"Systematic Rectification of Language Models via Dead-end Analysis","authors":["M Cao, M Fatemi, JCK Cheung, S Shabanian - arXiv preprint arXiv:2302.14003, 2023"],"snippet":"With adversarial or otherwise normal prompts, existing large language models (LLM) can be pushed to generate toxic discourses. One way to reduce the risk of LLMs generating undesired discourses is to alter the training of the LLM. This can be very …","url":["https://arxiv.org/pdf/2302.14003"]}
{"year":"2023","title":"Systems and Algorithms for Dynamic Graph Processing","authors":["K Ammar - 2023"],"snippet":"Data generated from human and systems interactions could be naturally represented as graph data. Several emerging applications rely on graph data, such as the semantic web, social networks, bioinformatics, finance, and trading among …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19195/Ammar_Khaled.pdf?sequence=3&isAllowed=y"]}
{"year":"2023","title":"Systems and Resources for Telugu: Question Answering and Summarization","authors":["P Ravva - 2023"],"snippet":"Natural language processing (NLP) is a bridge between the computer and human interactions in their natural language. NLP has wide variety of applications such as machine translation, text summarization, question-answering, sentiment analysis, etc …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.b93b1f715416394f.46696e616c5468657369735375626d697373696f6e5f50726979616e6b61202831292e706466.pdf"]}
{"year":"2023","title":"T-MARS: Improving Visual Representations by Circumventing Text Feature Learning","authors":["P Maini, S Goyal, ZC Lipton, JZ Kolter, A Raghunathan - arXiv preprint arXiv …, 2023"],"snippet":"… 46] datasets, there has been a growing interest in exploring improved strategies for selecting subsets of the common crawl that help learn better … Most recently, DataComp [14] was introduced as a benchmark challenge for subset selection from …","url":["https://arxiv.org/pdf/2307.03132"]}
{"year":"2023","title":"T3L: Translate-and-Test Transfer Learning for Cross-Lingual Text Classification","authors":["IJ Unanue, G Haffari, M Piccardi - arXiv preprint arXiv:2306.04996, 2023"],"snippet":"… 2021), all typically using hundreds of gigabytes or terabytes of pretraining data (eg, 2.5 TB of Common Crawl data for XLM-R). However, such large, pretrained multilingual models still suffer from significant performance limitations, particularly in …","url":["https://arxiv.org/pdf/2306.04996"]}
{"year":"2023","title":"T5G2P: Multilingual Grapheme-to-Phoneme Conversion with Text-to-Text Transfer Transformer","authors":["M Řezáčková, A Frémund, J Švec, J Matoušek - Asian Conference on Pattern …, 2023"],"snippet":"… The original Google’s T5-base English model Footnote 4 (labeled as t5-EN in our paper) was trained from Common Crawl data Footnote 5 . We replicated the same pre-processing procedure to obtain the data for other languages tested in the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47665-5_27"]}
{"year":"2023","title":"TabLib: A Dataset of 627M Tables with Context","authors":["G Eggert, K Huo, M Biven, J Waugh - arXiv preprint arXiv:2310.07875, 2023"],"snippet":"… An important caveat is that there may be a selection bias affecting this analysis, due to factors such as our exclusion of tables larger than 1 GB, Common Crawl’s truncation of large responses, parsing bugs and limitations, etc. We leave a more …","url":["https://arxiv.org/pdf/2310.07875"]}
{"year":"2023","title":"Tackling Fake News in Bengali: Unraveling the Impact of Summarization vs. Augmentation on Pre-trained Language Models","authors":["AS Chowdhury, GM Shahariar, AT Aziz, SM Alam… - arXiv preprint arXiv …, 2023"],"snippet":"With the rise of social media and online news sources, fake news has become a significant issue globally. However, the detection of fake news in low resource languages like Bengali has received limited attention in research. In this paper, we …","url":["https://arxiv.org/pdf/2307.06979"]}
{"year":"2023","title":"Tackling Hallucinations in Chart Summarization","authors":["S Obaid ul Islam - 2023"],"snippet":"… Pre-training models on large corpora like Common Crawl results in models learning language in its parameters. This is called parametric knowledge which helps improve the performance when the model is finetuned on a downstream task …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/179356/120437011.pdf?sequence=1"]}
{"year":"2023","title":"Tackling the multilingual and heterogeneous documents with the pre-trained language identifiers","authors":["MR Kanfoud, A Bouramoul - International Journal of Computers and Applications, 2023"],"snippet":"… The authors collected data from a non-profit foundation, Common Crawl, which explores the Web and provides data freely to the public. The collected datasets are heterogeneous and multilingual. The authors proposed a multithreaded pipelined …","url":["https://www.tandfonline.com/doi/abs/10.1080/1206212X.2023.2218236"]}
{"year":"2023","title":"TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in LLMs through Translation-Assisted Chain-of-Thought Processes","authors":["B Upadhayay, V Behzadan - arXiv preprint arXiv:2311.10797, 2023"],"snippet":"… Authors trained XLM-R model by increasing the training examples and training the cross-lingual presentations from more than 2 terabytes of Common Crawl data. Chi et al. [28] further improved these models using two discriminative pretraining …","url":["https://arxiv.org/pdf/2311.10797"]}
{"year":"2023","title":"TaCo: Targeted Concept Removal in Output Embeddings for NLP via Information Theory and Explainability","authors":["F Jourdan, L Béthune, A Picard, L Risser, N Asher - arXiv preprint arXiv:2312.06499, 2023"],"snippet":"… 2018) a dataset containing a subset of CommonCrawl data filtered to match the story-like style of Winograd schemas. Pre-training was performed on these data by randomly masking 15% of the words in each of the input sentences and then trying …","url":["https://arxiv.org/pdf/2312.06499"]}
{"year":"2023","title":"Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model","authors":["YT Lin, YN Chen - arXiv preprint arXiv:2311.17487, 2023"],"snippet":"… When we added approximately 9 billion tokens of CommonCrawl data, specifically filtered for Traditional Chinese content (zh-tw), the performance of TAIWAN-LLM unexpectedly declined. For the 13 billion parameter model, the Exact …","url":["https://arxiv.org/pdf/2311.17487"]}
{"year":"2023","title":"Take a Closer Look at Multilinguality! Improve Multilingual Pre-Training Using Monolingual Corpora Only","authors":["J Lu, Y Lu, J Zhang - Findings of the Association for Computational …, 2023"],"snippet":"… Pre-training Data We collect monolingual corpora from Common Crawl Corpus, which contains about 890GB data for 50 languages. Different from previous studies, we do not use any bilingual corpus. Following (Conneau and Lample…","url":["https://aclanthology.org/2023.findings-emnlp.190.pdf"]}
{"year":"2023","title":"Taken out of context: On measuring situational awareness in LLMs","authors":["L Berglund, AC Stickland, M Balesni, M Kaufmann… - arXiv preprint arXiv …, 2023"],"snippet":"We aim to better understand the emergence of `situational awareness' in large language models (LLMs). A model is situationally aware if it's aware that it's a model and can recognize whether it's currently in testing or deployment. Today's LLMs are …","url":["https://arxiv.org/pdf/2309.00667"]}
{"year":"2023","title":"Targeted and Troublesome: Tracking and Advertising on Children's Websites","authors":["Z Moti, A Senol, H Bostani, FZ Borgesius, V Moonsamy… - arXiv preprint arXiv …, 2023"],"snippet":"… Applying this classifier to over two million pages from the Common Crawl dataset, we compile a list of two thousand child-directed websites. Crawling these sites from five vantage points, we measure the prevalence of trackers, fingerprinting scripts …","url":["https://arxiv.org/pdf/2308.04887"]}
{"year":"2023","title":"Targeted Data Augmentation Improves Context-aware Neural Machine Translation","authors":["H Gete, T Etchegoyhen, G Labaka - Proceedings of Machine Translation Summit XIX …, 2023"],"snippet":"Progress in document-level Machine Translation is hindered by the lack of parallel training data that include context information. In this work, we evaluate the potential of data augmentation techniques to circumvent these limitations, showing that …","url":["https://aclanthology.org/2023.mtsummit-research.25.pdf"]}
{"year":"2023","title":"TASTA: Text‐Assisted Spatial and Temporal Attention Network for Video Question Answering","authors":["T Wang, B Hou, J Li, P Shi, B Zhang, H Snoussi - Advanced Intelligent Systems, 2022"],"snippet":"… GLoVe[34] is pretrained on the Common Crawl dataset and it maps each word (eg, the ith word) into a 300D feature vector (eg, ti ∈ ℝ300). Considering that the length of the video and the image size are not fixed, the video is preprocessed to a uniform …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202200131"]}
{"year":"2023","title":"Taxi1500: A Multilingual Dataset for Text Classification in 1500 Languages","authors":["C Ma, A ImaniGooghari, H Ye, E Asgari, H Schütze - arXiv preprint arXiv:2305.08487, 2023"],"snippet":"… massive data from Common Crawl in 104 languages, significantly boosting the performance and outperforming mBERT. Compared with XLM, XLM-R has a larger vocabulary size of 250K. Besides, the training data scales from Wikipedia to a larger …","url":["https://arxiv.org/pdf/2305.08487"]}
{"year":"2023","title":"Teach LLMs to Personalize--An Approach inspired by Writing Education","authors":["C Li, M Zhang, Q Mei, Y Wang, SA Hombaiah, Y Liang… - arXiv preprint arXiv …, 2023"],"snippet":"Personalized text generation is an emerging research area that has attracted much attention in recent years. Most studies in this direction focus on a particular domain by designing bespoke features or models. In this work, we propose a general …","url":["https://arxiv.org/pdf/2308.07968"]}
{"year":"2023","title":"TeamAmpa at SemEval-2023 Task 3: Exploring Multilabel and Multilingual RoBERTa Models for Persuasion and Framing Detection","authors":["A Pauli, R Sarabia, L Derczynski, I Assent - Proceedings of the The 17th International …, 2023"],"snippet":"This paper describes our submission to theSemEval 2023 Task 3 on two subtasks: detectingpersuasion techniques and framing. Bothsubtasks are multi-label classification problems. We present a set of experiments, exploring howto get robust …","url":["https://aclanthology.org/2023.semeval-1.117.pdf"]}
{"year":"2023","title":"Tech tapas-one byte at a time more about AI, machine learning and ChatGPT","authors":["F MacDowall - Australian Law Librarian, 2023"],"snippet":"… The Common Crawl corpus13 contains petabytes of data collected over 12 years of web … While it can be argued that the Common Crawl corpus is an accurate portrayal of the discourse of … Notably, the Common Crawl overrepresents those …","url":["https://search.informit.org/doi/pdf/10.3316/agispt.20230621090484"]}
{"year":"2023","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","authors":["G Yang, D Yu, C Zhu, S Hayou"],"snippet":"… , which we illustrate both theoretically and empirically on simple networks as well as Megatron transformer trained on Common Crawl. … We demonstrate this pedagogically on resnet with MLP blocks but also on Megatron transformer trained …","url":["https://arxiv.org/pdf/2310.02244"]}
{"year":"2023","title":"Testing the Depth of ChatGPT's Comprehension via Cross-Modal Tasks Based on ASCII-Art: GPT3. 5's Abilities in Regard to Recognizing and Generating ASCII-Art …","authors":["D Bayani - arXiv preprint arXiv:2307.16806, 2023"],"snippet":"… Thus, this is a form of ASCII-art for which GPT3.5 may have a substantial amount of varied training data as compiled in the common-crawl dataset11 and potentially other locations. Additionally, owing to its use in technical areas often as an aid to …","url":["https://arxiv.org/pdf/2307.16806"]}
{"year":"2023","title":"Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks","authors":["S Sarkar, L Lausen - arXiv preprint arXiv:2310.00789, 2023"],"snippet":"… . 2015) is a collection of about 125 million data tables extracted from the Common Crawl. 3. TAPEX: w use the dataset used in training the … The tables were extracted from the Common Crawl although the timeline of the pages of the common crawl …","url":["https://arxiv.org/pdf/2310.00789"]}
{"year":"2023","title":"TEXILA INTERNATIONAL JOURNAL OF ACADEMIC RESEARCH","authors":["NM Ndongala"],"snippet":"RAT-SQL is among the popular framework used in the Text-To-SQL challenges for jointly encoding the database relations and questions in a way to improve the semantic parser. In this work, we propose a light version of the RAT-SQL where we …","url":["https://www.texilajournal.com/academic-research/edition/161-volume10-issue2"]}
{"year":"2023","title":"Text Analytics Solutions for the Control of Fake News: Materials and Methods","authors":["E Ogbuju, T Abiodun, F Oladipo - International Journal of Open Information …, 2023"],"snippet":"The increase in the rate of internet and social media use has given rise to a lot of fake news and misinformation available online. The internet and social media have made information and communications flow to be faster and easier. On the other …","url":["http://injoit.org/index.php/j1/article/viewFile/1475/1408"]}
{"year":"2023","title":"Text augmentation for semantic frame induction and parsing","authors":["S Anwar, A Shelmanov, N Arefyev, A Panchenko… - Language Resources and …, 2023"],"snippet":"Semantic frames are formal structures describing situations, actions or events, eg, Commerce buy, Kidnapping, or Exchange. Each frame provides a set of frame elements or semantic roles corresponding to participants of the situation and lexical …","url":["https://link.springer.com/article/10.1007/s10579-023-09679-8"]}
{"year":"2023","title":"Text Content Moderation Model to Detect Sexually Explicit Content","authors":["SAN Murthy"],"snippet":"Our objective is to build a Transformer based classification model for the recognition of Sexually Explicit Speech and do a comparative analysis with other (fine-tuned) models in the Sexually Explicit domain. Our approach was to take an open-source …","url":["http://cs230.stanford.edu/projects_spring_2022/reports/127569181.pdf"]}
{"year":"2023","title":"Text Intimacy Analysis using Ensembles of Multilingual Transformers","authors":["T Chavan, V Patwardhan - arXiv preprint arXiv:2312.02590, 2023"],"snippet":"Intimacy estimation of a given text has recently gained importance due to the increase in direct interaction of NLP systems with humans. Intimacy is an important aspect of natural language and has a substantial impact on our everyday …","url":["https://arxiv.org/pdf/2312.02590"]}
{"year":"2023","title":"Text mining of scientific literature and the need for open access","authors":["M Vishwanath - 2023"],"snippet":"… We need a scientific analogue to Common-Crawl, an open repository of scientific articles for use in exploratory data analysis. Ironically, this argument is not new, and indeed, was anticipated as part of the original definition of open access given at the …","url":["https://osf.io/mf4pt/download"]}
{"year":"2023","title":"Text Summarization for Resource-Poor Languages: Datasets and Models for Multiple Indian Languages","authors":["VL Sireesha - 2023"],"snippet":"… model pre-trained on Common Crawl [7] data in 100 languages. XLM-R is created by training a Transformer-based masked language model on a hundred languages. • mT5: mT5 [77] is a multilingual variant of T5 model pre-trained on …","url":["https://cdn.iiit.ac.in/cdn/web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.957680cd46d4bccb.73697265657368612d7468657369732d7072657072696e74202831292e706466.pdf"]}
{"year":"2023","title":"Text Summarization of Medical Documents using Abstractive Techniques","authors":["E Lalitha, K Ramani, D Shahida, EVS Deepak… - 2023 2nd International …, 2023"],"snippet":"Medical researchers are exposed to enormous amounts of medical information in the form of medical news, clinical trial reports, research articles, etc. Researchers would need the documents' summaries that help them decide to do an in-depth study …","url":["https://ieeexplore.ieee.org/abstract/document/10140885/"]}
{"year":"2023","title":"Text, Speech, and Dialogue: 26th International Conference, TSD 2023, Pilsen, Czech Republic, September 4–6, 2023, Proceedings","authors":["K Ekštein"],"snippet":"The annual International Conference on Text, Speech and Dialogue (TSD), which emerged in 1998, constitutes a recognized platform for presenting and discussing stateof-the-art technology and recent achievements in the computer processing of …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=enjSEAAAQBAJ&oi=fnd&pg=PP7&dq=commoncrawl&ots=eW1UKfh2RN&sig=PrJzRFJpibqDn4L9UvBekfOn5Qg"]}
{"year":"2023","title":"Text-based Patent-Quality Prediction Using Multi-Section Attention","authors":["X Krant - 2023"],"snippet":"The number of patents has increased tremendously in recent years and statistics derived from patents have become the standard measurement for innovation. Patents statistics are widely available and correlate well with patent valuation and …","url":["https://fse.studenttheses.ub.rug.nl/29717/1/Scriptie_X_Krant_s2955156_final.pdf"]}
{"year":"2023","title":"Text-Blueprint: An Interactive Platform for Plan-based Conditional Generation","authors":["F Huot, J Maynez, S Narayan, RK Amplayo, K Ganchev… - Proceedings of the 17th …, 2023"],"snippet":"… -sourced answer spans from Wikipedia, and matched with passages from web documents from Common Crawl. AQuaMuse uses the answer passages as summaries with the passages extracted from Common Crawl as the input documents …","url":["https://aclanthology.org/2023.eacl-demo.13.pdf"]}
{"year":"2023","title":"Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks","authors":["X Zhang, H Hong, Y Hong, P Huang, B Wang, Z Ba… - arXiv preprint arXiv …, 2023"],"snippet":"The language models, especially the basic text classification models, have been shown to be susceptible to textual adversarial attacks such as synonym substitution and word insertion attacks. To defend against such attacks, a growing body of …","url":["https://arxiv.org/pdf/2307.16630"]}
{"year":"2023","title":"Text-Guided Image Generation for Railway Intrusion Anomaly Detection","authors":["J Chen, C Zhang, X Feng, Y Liu - 2023 IEEE International Conference on Unmanned …, 2023"],"snippet":"Railway intrusion are characterized by strong suddenness, high unpredictability and many disturbing factors, which are key factors affecting railway safety. Currently, the deep neural network-based intrusion object detection algorithm relies on the …","url":["https://ieeexplore.ieee.org/abstract/document/10318477/"]}
{"year":"2023","title":"Text-guided Image-and-Shape Editing and Generation: A Short Survey","authors":["CKT Chao, Y Gingold - arXiv preprint arXiv:2304.09244, 2023"],"snippet":"… CLIP is trained on 400 million text-image pairs from common-crawl dataset with contrastive objectives to learn image representations from text. The overall framework can be seen in Figure 1. To be more specific, the image encoder is …","url":["https://arxiv.org/pdf/2304.09244"]}
{"year":"2023","title":"That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?","authors":["J Lee, A Liu, O Ahia, H Gonen, NA Smith - arXiv preprint arXiv:2310.14610, 2023"],"snippet":"… Moreover, we observe that the differences between LMs and MT-specific models become less pronounced for more under-resourced languages (the languages are ordered left to right based on count of pages in Common Crawl9). 9https://commoncrawl.github.io …","url":["https://arxiv.org/pdf/2310.14610"]}
{"year":"2023","title":"The (Undesired) Attenuation of Human Biases by Multilinguality","authors":["C España-Bonet, A Barrón-Cedeño - Proceedings of the 2022 Conference on …, 2022"],"snippet":"… CCWP: Models trained on Common Crawl and Wikipedia using CBOW with position weights and subword information (Grave et al.… We also build 5 static in-house word embeddings on Common Crawl using a subset of the CC-100 corpus (Conneau et al.…","url":["https://aclanthology.org/2022.emnlp-main.133.pdf"]}
{"year":"2023","title":"The Algorithmic Internet: Culture, capture, corruption","authors":["C Lu"],"snippet":"The internet is haunted by ailing social media platforms with declining engagement and perpetual feeds of quick dopamine hits; large machine learning models are contaminated with an insurmountable sea of toxicity and cul-de-sacs of gibberish …","url":["https://www.paradigmtrilogy.com/assets/documents/issue-02/christina-lu--the-algorithmic-internet.pdf"]}
{"year":"2023","title":"The Axiom of Choice and Its Influence on LLM Hallucinations: An Exploration","authors":["R Kaushik - 2023"],"snippet":"The Axiom of Choice (AoC), a foundational proposition in set theory, allows for the selection of elements from a collection of non-empty sets without specifying the selection method. Surprisingly, this mathematical principle offers insights into the …","url":["https://www.researchgate.net/profile/Rahul-Kaushik-15/publication/375074101_The_Axiom_of_Choice_and_Its_Influence_on_LLM_Hallucinations_An_Exploration/links/653f7d38ff8d8f507cd86e37/The-Axiom-of-Choice-and-Its-Influence-on-LLM-Hallucinations-An-Exploration.pdf"]}
{"year":"2023","title":"The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants","authors":["L Bandarkar, D Liang, B Muller, M Artetxe, SN Shukla… - arXiv preprint arXiv …, 2023"],"snippet":"We present Belebele, a multiple-choice machine reading comprehension (MRC) dataset spanning 122 language variants. Significantly expanding the language coverage of natural language understanding (NLU) benchmarks, this dataset …","url":["https://arxiv.org/pdf/2308.16884"]}
{"year":"2023","title":"The BETTER Cross-Language Datasets","authors":["I Soboroff - Proceedings of the 46th International ACM SIGIR …, 2023"],"snippet":"… The document collections are taken from CommonCrawl.The phase 1 documents were collected by MITRE, and for phases 2 and 3 by ARLIS. Care was taken to identify subsets of the CommonCrawl collection that were likely to contain topical …","url":["https://dl.acm.org/doi/abs/10.1145/3539618.3591910"]}
{"year":"2023","title":"The BETTER Cross-Language Information Retrieval Datasets","authors":["I Soboroff - 2023"],"snippet":"… The document collections are taken from CommonCrawl.The phase 1 documents were collected by MITRE, and for phases 2 and 3 by ARLIS. Care was taken to identify subsets of the CommonCrawl collection that were likely to contain topical …","url":["https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936449"]}
{"year":"2023","title":"The Claire French Dialogue Dataset","authors":["J Hunter, J Louradour, V Rennard, I Harrando… - arXiv preprint arXiv …, 2023"],"snippet":"We present the Claire French Dialogue Dataset (CFDD), a resource created by members of LINAGORA Labs in the context of the OpenLLM France initiative. CFDD is a corpus containing roughly 160 million words from transcripts and stage plays in …","url":["https://arxiv.org/pdf/2311.16840"]}
{"year":"2023","title":"The Cultivated Practices of Text-to-Image Generation","authors":["J Oppenlaender - arXiv preprint arXiv:2306.11393, 2023"],"snippet":"Humankind is entering a novel creative era in which anybody can synthesize digital information using generative artificial intelligence (AI). Text-to-image generation, in particular, has become vastly popular and millions of practitioners produce AI-generated …","url":["https://arxiv.org/pdf/2306.11393"]}
{"year":"2023","title":"The Cultural Devaluation of Feminized Work: The Evolution of Occupational Prestige and Gender Typing in the United States, 1900-2019","authors":["W Jiang - 2023"],"snippet":"… to head and visual modality from the Common Crawl embedding are positively associated with an occupation’s survey-based prestige. … Index (ISEI) and prestige measures from the embeddings of the Common Crawl (CC) corpus. Table 1 …","url":["https://osf.io/preprints/socarxiv/8q3ca/download"]}
{"year":"2023","title":"The Diagnostic and Triage Accuracy of the GPT-3 Artificial Intelligence Model","authors":["DM Levine, R Tuwani, B Kompa, A Varma… - medRxiv, 2023"],"snippet":"Importance: Artificial intelligence (AI) applications in health care have been effective in many areas of medicine, but they are often trained for a single task using labeled data, making deployment and generalizability challenging. Whether a general-purpose …","url":["https://www.medrxiv.org/content/10.1101/2023.01.30.23285067.full.pdf"]}
{"year":"2023","title":"The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers","authors":["H Li, N Vincent, S Chancellor, B Hecht - arXiv preprint arXiv:2305.13238, 2023"],"snippet":"Many recent technological advances (eg ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with computing systems or scraped from the web (eg …","url":["https://arxiv.org/pdf/2305.13238"]}
{"year":"2023","title":"The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models","authors":["L Hagström, D Saynova, T Norlund, M Johansson… - arXiv preprint arXiv …, 2023"],"snippet":"Large Language Models (LLMs) make natural interfaces to factual knowledge, but their usefulness is limited by their tendency to deliver inconsistent answers to semantically equivalent questions. For example, a model might predict both \"Anne …","url":["https://arxiv.org/pdf/2311.01307"]}
{"year":"2023","title":"The Effects of Corpus Choice and Morphosyntax on Multilingual Space Induction","authors":["V Ravishankar, J Nivre - Findings of the Association for Computational …, 2022"],"snippet":"… There is also a clear difference between Wikipedia and Common Crawl; in general, we find that correlations tend to be either weaker or less significant with Common Crawl than with Wikipedia. We hypothesise that this is due to Wikipedia …","url":["https://aclanthology.org/2022.findings-emnlp.304.pdf"]}
{"year":"2023","title":"The emergence of autolography: the 'magical'invocation of images from text through AI","authors":["C Chesher, C Albarrán-Torres - Media International Australia, 2023"],"snippet":"In mid-2022, AI systems automatically translating text into evocative original images became an internet sensation. People compared it to magic: invoking an uncannily competent artist–magician. We call it ‘autolography’ from the Greek ‘automatos + …","url":["https://journals.sagepub.com/doi/pdf/10.1177/1329878X231193252"]}
{"year":"2023","title":"The Falcon Series of Open Language Models","authors":["E Almazrouei, H Alobeidli, A Alshamsi, A Cappelli… - arXiv preprint arXiv …, 2023"],"snippet":"… CommonCrawl), and evaluate on English tasks. Each data split uses a dedicated tokenizer. … Latin alphabet, and sufficient presence in CommonCrawl to collect at least 10 billion tokens. … Since training of the models was started before we had …","url":["https://arxiv.org/pdf/2311.16867"]}
{"year":"2023","title":"The Future of AI-Assisted Writing","authors":["CA Pereira, T Komarlu, W Mobeirek - arXiv preprint arXiv:2306.16641, 2023"],"snippet":"The development of Natural Language Generation models has led to the creation of powerful Artificial Intelligence-assisted writing tools. These tools are capable of predicting users' needs and actively providing suggestions as they write. In this work …","url":["https://arxiv.org/pdf/2306.16641"]}
{"year":"2023","title":"The Future of the Human–Machine Interface (HMI) in Society 5.0","authors":["D Mourtzis, J Angelopoulos, N Panopoulos - Future Internet, 2023"],"snippet":"The blending of human and mechanical capabilities has become a reality in the realm of Industry 4.0. Enterprises are encouraged to design frameworks capable of harnessing the power of human and technological resources to enhance the era of …","url":["https://www.mdpi.com/1999-5903/15/5/162"]}
{"year":"2023","title":"The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages","authors":["B Muller, B Alastruey, P Hansanti, E Kalbassi… - arXiv preprint arXiv …, 2023"],"snippet":"… level for Common Crawl. We segment each sample at the word level using Stanza tokenizer available in the given language (Qi et al.… In addition, we run the pipeline on a sample of Common CrawlCommon Crawl is a snapshot of crawlable …","url":["https://arxiv.org/pdf/2308.16871"]}
{"year":"2023","title":"The generative art community bridging between UNESCO Heritage and AI-generated works: an interview with Celestino Soddu and Enrica Colabella","authors":["S Park - Proceedings of GA2023, XXVI Generative Art …, 2023"],"snippet":"… Around 60% of ChatGPT-3’s dataset was based on af iltered version of the web-crawled data of Common Crawl [1], a non -profit organisation that scraps publicly available textual data on the internet such as books, web pages and ar ticles. Most of the tasks …","url":["https://wrap.warwick.ac.uk/181879/1/WRAP-Generative-art-community-bridging-UNESCO-heritage-AI-interview-23.pdf"]}
{"year":"2023","title":"The Ghost in the Machine: Generating Beliefs with Large Language Models","authors":["JL Bybee"],"snippet":"I introduce a methodology to generate economic expectations by applying large language models to historical news. Leveraging this methodology, I make three key contributions.(1) I show generated expectations closely match existing survey …","url":["https://lelandbybee.com/files/LLM.pdf"]}
{"year":"2023","title":"The Governance Challenge Posed by Large Learning Models","authors":["SA Aaronson - 2023"],"snippet":"On August 24, 2023, the Office of the Australian Information Commissioner (OAIC) and 11 of its international data protection and privacy counterparts released a joint statement on web scraping (data collected by a bot from a wide range of websites) …","url":["https://www2.gwu.edu/~iiep/assets/docs/papers/2023WP/AaronsonIIEP2023-07.pdf"]}
{"year":"2023","title":"The Great Awokening as a Global Phenomenon","authors":["D Rozado - arXiv preprint arXiv:2304.01596, 2023"],"snippet":"… The text content of the analyzed articles is available on the web domains of the respective media outlets and often also in Internet cache repositories such as Common Crawl, Google cache or the Internet Archive. Our content analysis is limited …","url":["https://arxiv.org/pdf/2304.01596"]}
{"year":"2023","title":"The History and Future of Human–Robot Communication","authors":["F Shkurti - The SAGE Handbook of Human–Machine …, 2023"]}
{"year":"2023","title":"The House that Looked Like It Should Collapse. Natural Language Processing for Architectural Design","authors":["N Gaudillière-Jami - … Conference on Computer-Aided Architectural Design …, 2023"],"snippet":"… It has been trained on billions of online texts, coming from databases such as Common Crawl, Books2 or Wikipedia. The texts it generates are therefore based on a very large range of information, including about architecture. While only being word-based …","url":["https://link.springer.com/chapter/10.1007/978-3-031-37189-9_7"]}
{"year":"2023","title":"The Impact of Arabic Diacritization on Word Embeddings","authors":["M Abbache, A Abbache, J Xu, F Meziane, X Wen - ACM Transactions on Asian and …, 2023"],"snippet":"Word embedding is used to represent words for text analysis. It plays an essential role in many Natural Language Processing (NLP) studies and has hugely contributed to the extraordinary developments in the field in the last few years. In …","url":["https://dl.acm.org/doi/pdf/10.1145/3592603"]}
{"year":"2023","title":"The Impact of Depth and Width on Transformer Language Model Generalization","authors":["J Petty, S van Steenkiste, I Dasgupta, F Sha, D Garrette… - arXiv preprint arXiv …, 2023"],"snippet":"To process novel sentences, language models (LMs) must generalize compositionally -- combine familiar elements in new ways. What aspects of a model's structure promote compositional generalization? Focusing on transformers …","url":["https://arxiv.org/pdf/2310.19956"]}
{"year":"2023","title":"The Impact of GloVe and Word2Vec Word-Embedding Technologies on Bug Localization with Convolutional Neural Network","authors":["AS Al-Aidaroos"],"snippet":"In the field of software engineering, software quality assurance faces many challenges, including overcoming the problem of identifying errors in the source code. Finding the location of the error in the source code is a very important process …","url":["https://www.researchgate.net/profile/Ahmed-Al-Aidaroos/publication/367179325_The_Impact_of_GloVe_and_Word2Vec_Word-Embedding_Technologies_on_Bug_Localization_with_Convolutional_Neural_Network/links/63e12e5bc97bd76a827660ea/The-Impact-of-GloVe-and-Word2Vec-Word-Embedding-Technologies-on-Bug-Localization-with-Convolutional-Neural-Network.pdf"]}
{"year":"2023","title":"The Importance of Context in the Evaluation of Word Embeddings: The Effects of Antonymy and Polysemy","authors":["J Fodor, S De Deyne, S Suzuki"],"snippet":"Word embeddings are widely used for diverse applications in natural language processing. Despite extensive research, it is unclear when they succeed or fail to capture human judgements of semantic relatedness and similarity. In this study, we …","url":["https://iwcs.pimoid.fr/11.pdf"]}
{"year":"2023","title":"The Less the Merrier? Investigating Language Representation in Multilingual Models","authors":["HH Nigatu, AL Tonja, J Kalita - arXiv preprint arXiv:2310.13228, 2023"],"snippet":"… 2019) is a multilingual Transformer-based MLM trained on the Common Crawl data for 100 languages. To balance data between English and other languages, the XLM-R uses one dump for English and 12 dumps for all other languages. … Filtered …","url":["https://arxiv.org/pdf/2310.13228"]}
{"year":"2023","title":"The Library & Generative AI","authors":["N Gustafson-Sundell, M McCullough - 2023"],"snippet":"A demonstration of several AI tools, including ChatGPT, ChatPDF, Consensus, and more. The focus of the session is on potential student uses of the tools and related library initiatives, so we address the limits of ChatGPT as an information source …","url":["https://cornerstone.lib.mnsu.edu/cgi/viewcontent.cgi?article=1205&context=lib_services_fac_pubs"]}
{"year":"2023","title":"The Mental Representation of Structured Auditory Sequences in Memory","authors":["O Raccah - 2023"],"snippet":"The capacity to remember and retrieve sequences of items or everyday experiences is fundamental to human intelligence. The goal of this research is to understand how the episodic memory system supports the integration, representation, and retrieval of …","url":["https://search.proquest.com/openview/1ad1d94e88a7df947828924bc4fafb4b/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"The more","authors":["KS Yong, JSY Liew - Journal of Intelligent Information Systems, 2023"],"snippet":"… The main difference between the two InferSent model is one uses GloVe word embeddings trained on Common Crawl 840B (InferSent-GloVe) and the other uses fastText word embeddings trained on Common Crawl 600B (InferSent-fastText). …","url":["https://link.springer.com/article/10.1007/s10844-023-00791-3"]}
{"year":"2023","title":"The Nordic Pile: A 1.2 TB Nordic Dataset for Language Modeling","authors":["J Öhman, S Verlinden, A Ekgren, AC Gyllensten… - arXiv preprint arXiv …, 2023"],"snippet":"… We decided that our Nordic-language datasets were more prone to include many duplicate documents since we included several data sources from Common Crawl that may overlap for these languages. So, our English data was deduplicated intra-shard …","url":["https://arxiv.org/pdf/2303.17183"]}
{"year":"2023","title":"The Ouroboros Threat","authors":["JM Vukov, TL Joseph, G Lebkuecher, M Ramirez… - The American Journal of …, 2023"],"snippet":"Jorge Luis Borges introduces the mythical ouroboros as follows:“A third-century Greek amulet, to be found today in the British Museum, gives us an image that can better illustrate that infinitude: the serpent that bites its own tail”(Borges 2005). In this …","url":["https://www.tandfonline.com/doi/full/10.1080/15265161.2023.2250284"]}
{"year":"2023","title":"The Perils & Promises of Fact-checking with Large Language Models","authors":["D Quelle, A Bovet - arXiv preprint arXiv:2310.13549, 2023"],"snippet":"… The GPT models are trained on vast amounts of unstructured textual data like the common crawl data-set, which is the largest data-set to be included in the training. Common Crawl is a web archive that consists of terabytes of data collected since …","url":["https://arxiv.org/pdf/2310.13549"]}
{"year":"2023","title":"The perpetual motion machine of AI-generated data and the distraction of ChatGPT-as-scientist","authors":["J Listgarten - arXiv preprint arXiv:2312.00818, 2023"],"snippet":"Since ChatGPT works so well, are we on the cusp of solving science with AI? Is not AlphaFold2 suggestive that the potential of LLMs in biology and the sciences more broadly is limitless? Can we use AI itself to bridge the lack of data in the sciences in …","url":["https://arxiv.org/pdf/2312.00818"]}
{"year":"2023","title":"The Photographic Pipeline of Machine Vision; or, Machine Vision's Latent Photographic Theory","authors":["N Malevé, K Sluis - Critical AI, 2023"],"snippet":"Despite computer vision's extensive mobilization of cameras, photographers, and viewing subjects, photography's place in machine vision remains undertheorized. This article illuminates an operative theory of photography that exists in a latent form …","url":["https://read.dukeupress.edu/critical-ai/article-abstract/doi/10.1215/2834703X-10734066/382465"]}
{"year":"2023","title":"The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data Only","authors":["G Penedo, Q Malartic, D Hesslow, R Cojocaru… - Thirty-seventh Conference …, 2023"],"snippet":"… Although this is only a 135 narrow subset of the kind of pages making up CommonCrawl, we found this finding to hold more 136 broadly. We use trafilatura for text extraction, and apply extra formatting via regular expressions: 137 we limit new …","url":["https://openreview.net/pdf?id=kM5eGcdCzq"]}
{"year":"2023","title":"The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only","authors":["G Penedo, Q Malartic, D Hesslow, R Cojocaru…"],"snippet":"… Although this is only a narrow subset of the kind of pages making up CommonCrawl, we found this finding to hold more broadly. We use trafilatura … in the processed CommonCrawl data were identified as English. We find the …","url":["https://falconllm.tii.ae/Falcon_LLM_RefinedWeb.pdf"]}
{"year":"2023","title":"The Role of Codeword-to-Class Assignments in Error-Correcting Codes: An Empirical Study","authors":["I Evron, O Onn, TW Orzech, H Azeroual, D Soudry - arXiv preprint arXiv:2302.05334, 2023"],"snippet":"Error-correcting codes (ECC) are used to reduce multiclass classification tasks to multiple binary classification subproblems. In ECC, classes are represented by the rows of a binary matrix, corresponding to codewords in a codebook. Codebooks are …","url":["https://arxiv.org/pdf/2302.05334"]}
{"year":"2023","title":"The Role of Pre-training Data in Transfer Learning","authors":["R Entezari, M Wortsman, O Saukh, MM Shariatnia… - arXiv preprint arXiv …, 2023"],"snippet":"… Common crawl. https://commoncraw .org/. Accessed: 2022-09-20. … 2021): The images and corresponding alt-texts come from web pages collected by Common Crawl (Com) between 2014 and 2021. We randomly select a subset of 2.7M and …","url":["https://arxiv.org/pdf/2302.13602"]}
{"year":"2023","title":"The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages","authors":["C Zhang, KD Doan, Q Liao, M Abdul-Mageed - arXiv preprint arXiv:2310.14557, 2023"],"snippet":"Instruction tuned large language models (LLMs), such as ChatGPT, demonstrate remarkable performance in a wide range of tasks. Despite numerous recent studies that examine the performance of instruction-tuned LLMs on various NLP benchmarks …","url":["https://arxiv.org/pdf/2310.14557"]}
{"year":"2023","title":"The social construction of datasets: On the practices, processes and challenges of dataset creation for machine learning","authors":["W Orr, K Crawford - 2023"],"snippet":"Despite the critical role that datasets play in how systems make predictions and interpret the world, the dynamics of their construction are not well understood. Drawing on a corpus of interviews with dataset creators, we uncover the messy and …","url":["https://osf.io/preprints/socarxiv/8c9uh/download"]}
{"year":"2023","title":"The Three Terms Task-an open benchmark to compare human and artificial semantic representations","authors":["V Borghesani, J Armoza, MN Hebart, P Bellec… - Scientific Data, 2023"],"snippet":"… A fasttext 32 model trained on Common Crawl with subword information. Finally, three additional fasttext 32,39,40 models trained on … First, fasttext models outperform glove ones, except for the fasttext model trained on Common Crawl. As a …","url":["https://www.nature.com/articles/s41597-023-02015-3"]}
{"year":"2023","title":"The Use of a Large Language Model for Cyberbullying Detection. Analytics 2023, 2, 694–707","authors":["B Ogunleye, B Dharmaraj - 2023"],"snippet":"… It was trained on 100 languages from 2.5 TB of filtered common crawl data. The “RoBERTa” part in XLM-RoBERTa originates from the fact that it uses the identical training procedures as the monolingual RoBERTa model, with the Masked Language Model …","url":["https://www.academia.edu/download/106522086/analytics_02_00038_6_.pdf"]}
{"year":"2023","title":"The Utility of Large Language Models and Generative AI for Education Research","authors":["A Katz, U Shakir, B Chambers - arXiv preprint arXiv:2305.18125, 2023"],"snippet":"… Typically pre-trained on extensive text corpora (eg, a common crawl of the web consisting of billions of tokens of text) and fine-tuned for tasks such as question-answering or text classification [1], LLMs are distinguished by their capacity to seemingly …","url":["https://arxiv.org/pdf/2305.18125"]}
{"year":"2023","title":"The Value of Web Data Scraping: An Application to TripAdvisor","authors":["G Barbera, L Araujo, S Fernandes - Big Data and Cognitive Computing, 2023"],"snippet":"Social Media Analytics (SMA) is more and more relevant in today’s market dynamics. However, it is necessary to use it wisely, either in promoting any kind of product/brand, or interacting with customers. This requires its effective understanding and …","url":["https://www.mdpi.com/2504-2289/7/3/121"]}
{"year":"2023","title":"The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation","authors":["DN Manh, NL Hai, ATV Dau, AM Nguyen, K Nghiem… - arXiv preprint arXiv …, 2023"],"snippet":"We present The Vault, an open-source, large-scale code-text dataset designed to enhance the training of code-focused large language models (LLMs). Existing open-source datasets for training code-based LLMs often face challenges in terms of size, quality (due …","url":["https://arxiv.org/pdf/2305.06156"]}
{"year":"2023","title":"The Web Can Be Your Oyster for Improving Language Models","authors":["J Li, T Tang, WX Zhao, J Wang, JY Nie, JR Wen - Findings of the Association for …, 2023"],"snippet":"… Common Crawl snapshot which covers a wide range of 134M web documents and finally yields 906M passages of 100 tokens. CCNet processes Common Crawl … an analysis of undesirable content in the common crawl corpus. In Proceedings of …","url":["https://aclanthology.org/2023.findings-acl.46.pdf"]}
{"year":"2023","title":"The Web Can Be Your Oyster for Improving Large Language Models","authors":["J Li, T Tang, WX Zhao, J Wang, JY Nie, JR Wen - arXiv preprint arXiv:2305.10998, 2023"],"snippet":"… Common Crawl snapshot which covers a wide range of 134M web documents and finally yields 906M passages of 100 tokens. CCNet processes Common Crawl … an analysis of undesirable content in the common crawl corpus. In Proceedings of …","url":["https://arxiv.org/pdf/2305.10998"]}
{"year":"2023","title":"The Web Data Commons Schema. org Data Set Series","authors":["A Brinkmann, A Primpeli, C Bizer - Companion Proceedings of the ACM Web …, 2023"],"snippet":"… The Web Data Commons project has been extracting schema.org data from the Common Crawl every year since 2013 and offers the extracted data for public download in the form of the schema.org data set series. The latest release in the …","url":["https://dl.acm.org/doi/abs/10.1145/3543873.3587331"]}
{"year":"2023","title":"Theoretical Considerations on AI-based Business Models for Lexicography","authors":["H Køhler Simonsen - Lexicographica, 2023"],"snippet":"AI-generated text production is on the rise Zandan (2020), and AI writers seem to be playing an increasingly important role in marketing, L2 text production, lexicography and language teaching, cf. Simonsen (2020b; 2021a; 2022a; 2022b; Sharples/Pérez …","url":["https://www.degruyter.com/document/doi/10.1515/lex-2023-0013/html"]}
{"year":"2023","title":"There's no Data Like Better Data: Using QE Metrics for MT Data Filtering","authors":["JT Peter, D Vilar, D Deutsch, M Finkelstein, J Juraska… - arXiv preprint arXiv …, 2023"],"snippet":"Quality Estimation (QE), the evaluation of machine translation output without the need of explicit references, has seen big improvements in the last years with the use of neural metrics. In this paper we analyze the viability of using QE metrics for …","url":["https://arxiv.org/pdf/2311.05350"]}
{"year":"2023","title":"This Is a Local Domain: On Amassing Country-Code Top-Level Domains from Public Data","authors":["R Sommese, R van Rijswijk-Deij, M Jonker - arXiv preprint arXiv:2309.01441, 2023"],"snippet":"… For Common Crawl we consider data for crawl snapshots dated between June 2017 and June 2023 (inclusive). There are 58 such snapshots, collectively accounting for 127 million registered domain names. The combined total number of …","url":["https://arxiv.org/pdf/2309.01441"]}
{"year":"2023","title":"Thou Shalt Not Reject: Analyzing Accept-Or-Pay Cookie Banners on the Web","authors":["A Rasaii, D Gosain, O Gasser - 2023"],"snippet":"Privacy regulations have led to many websites showing cookie banners to their users. Usually, cookie banners present the user with the option to “accept” or “reject” cookies. Recently, a new form of paywall-like cookie banner has taken hold on the …","url":["https://www.devashishgosain.com/assets/files/paper-cameraready.pdf"]}
{"year":"2023","title":"TiBERT: A Non-autoregressive Pre-trained Model for Text Editing","authors":["B Wang, Z Wang, W Che, D Wu, R Zhang, B Wang… - … International Conference on …, 2023"],"snippet":"Text editing refers to the task of creating new sentences by altering existing text through methods such as replacing, inserting, or deleting. Two commonly used techniques for text editing are Seq2Seq and sequence labeling. The Seq2Seq …","url":["https://link.springer.com/chapter/10.1007/978-3-031-44699-3_2"]}
{"year":"2023","title":"TiC-CLIP: Continual Training of CLIP Models","authors":["S Garg, M Farajtabar, H Pouransari, R Vemulapalli… - arXiv preprint arXiv …, 2023"],"snippet":"… OpenCLIP models (eg, models trained on Datacomp and LAION-5B) have been trained on data curated from Common Crawl. Since the retrieval tasks we constructed are built on top of data curated from Common Crawl, one may argue …","url":["https://arxiv.org/pdf/2310.16226"]}
{"year":"2023","title":"TIL TA'LIMIDA RAQAMLI TEXNOLOGIY VA SUN'IY INTELLEKT VOSITALARIDAN FOYDALANISH","authors":["M Shahista - Innovations in Technology and Science Education, 2023"],"snippet":"… Algoritmni o’qitish uchun ingliz tilidagi 570 Gb hajmdagi matndan foydalanigan – matnlar Vikipediyadan, Common Crawl loyihasidan, ikkita kitoblar datasetidan va WebText2 datasetdagi web-sahifalardan olingan. Lekin bunda rus tilidagi matnlar …","url":["https://humoscience.com/index.php/itse/article/download/711/1277"]}
{"year":"2023","title":"TIL TA'LIMIDA RAQAMLI TEXNOLOGIYALARDAN FOYDALANISH USUL VA VOSITALARI","authors":["R Ayupov, S Maksimkulava, G Baltabaeva - Евразийский журнал академических …, 2023"],"snippet":"… Algoritmni o’qitish uchun ingliz tilidagi 570 Gb hajmdagi matndan foydalanigan – matnlar Vikipediyadan, Common Crawl loyihasidan, ikkita kitoblar datasetidan va WebText2 datasetdagi web-sahifalardan olingan. Lekin bunda rus tilidagi matnlar …","url":["https://in-academy.uz/index.php/ejar/article/download/14466/10065"]}
{"year":"2023","title":"TinyStories: How Small Can Language Models Be and Still Speak Coherent English?","authors":["R Eldan, Y Li - arXiv preprint arXiv:2305.07759, 2023"],"snippet":"Language models (LMs) are powerful tools for natural language processing, but they often struggle to produce coherent and fluent text when they are small. Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can rarely …","url":["https://arxiv.org/pdf/2305.07759"]}
{"year":"2023","title":"TKG: Telecom Knowledge Governance Framework for LLM Application","authors":["H Cai, S Wu - 2023"],"snippet":"… 15], such as Common Crawl and Wikipedia, which offer limited exposure to domain-specific resources. In telecommunications, there exist numerous manuals, delivery documents, and fault diagnosis cases related to communication equipment …","url":["https://www.researchsquare.com/article/rs-3252192/latest.pdf"]}
{"year":"2023","title":"TMD-BERT: A Transformer-Based Model for Transportation Mode Detection","authors":["I Drosouli, A Voulodimos, P Mastorocostas, G Miaoulis… - Electronics, 2023"],"snippet":"… This feature led to the development of pre-trained systems such as BERT (Bidirectional Encoder Representations from Transformers) [23] which was trained with large language datasets, such as the Wikipedia Corpus and Common Crawl. Thus …","url":["https://www.mdpi.com/2090966"]}
{"year":"2023","title":"TMD-NER: Turkish multi-domain named entity recognition for informal texts","authors":["SF Yilmaz, FB Mutlu, I Balaban, SS Kozat - Signal, Image and Video Processing, 2023"],"snippet":"We examine named entity recognition (NER), an essential and commonly used first step in many natural language processing tasks, including chatbots and language translation. We focus on the application of NER to texts that have a lot of noise, such …","url":["https://link.springer.com/article/10.1007/s11760-023-02898-0"]}
{"year":"2023","title":"tmn at SemEval-2023 Task 9: Multilingual Tweet Intimacy Detection using XLM-T, Google Translate, and Ensemble Learning","authors":["A Glazkova - arXiv preprint arXiv:2304.04054, 2023"],"snippet":"The paper describes a transformer-based system designed for SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis. The purpose of the task was to predict the intimacy of tweets in a range from 1 (not intimate at all) to 5 (very intimate). The …","url":["https://arxiv.org/pdf/2304.04054"]}
{"year":"2023","title":"To token or not to token: A Comparative Study of Text Representations for Cross-Lingual Transfer","authors":["MM Rahman, FA Sakib, F Faisal, A Anastasopoulos - arXiv preprint arXiv:2310.08078, 2023"],"snippet":"Choosing an appropriate tokenization scheme is often a bottleneck in low-resource cross-lingual transfer. To understand the downstream implications of text representation choices, we perform a comparative analysis on language models …","url":["https://arxiv.org/pdf/2310.08078"]}
{"year":"2023","title":"Token-level Identification of Multiword Expressions using Pre-trained Multilingual Language Models","authors":["R Swaminathan, P Cook - Proceedings of the 19th Workshop on Multiword …, 2023"],"snippet":"In this paper, we consider novel cross-lingual settings for multiword expression (MWE) identification (Ramisch et al., 2020) and idiomaticity prediction (Tayyar Madabushi et al., 2022) in which systems are tested on languages that are unseen during training …","url":["https://aclanthology.org/2023.mwe-1.1.pdf"]}
{"year":"2023","title":"Tokenization and the Noiseless Channel","authors":["V Zouhar, C Meister, JL Gastaldi, L Du, M Sachan… - arXiv preprint arXiv …, 2023"],"snippet":"… of 0.78 with BLEU on German → English MT (1M parallel sentences from CommonCrawl). This stands in contrast to Shannon entropy or expected … We use the English→German CommonCrawl dataset in all experiments. The specifics of the …","url":["https://arxiv.org/pdf/2306.16842"]}
{"year":"2023","title":"Tokenizer Choice For LLM Training: Negligible or Crucial?","authors":["M Ali, M Fromm, K Thellmann, R Rutmann…"],"snippet":"The recent success of Large Language Models (LLMs) has been predominantly driven by curating the training dataset composition, scaling of model architectures and dataset sizes and advancements in pretraining objectives, leaving tokenizer …","url":["https://arxiv.org/pdf/2310.08754"]}
{"year":"2023","title":"Too Legal; Didn't Read (TLDR): Summarization of Court Opinions","authors":["A Ghimire, R Shrestha, J Edwards - 2023 Intermountain Engineering, Technology and …, 2023"],"snippet":"… The majority of data in the PEGASUS project come from web common crawl, social media, and news. It however also includes the BillSum dataset [17]. BillSum (Kornilova & Eidelman, 2019) contains 23k US Congressional bills and human-written …","url":["https://ieeexplore.ieee.org/abstract/document/10152119/"]}
{"year":"2023","title":"Topical Clustering of Unlabeled Transformer-Encoded Researcher Activity","authors":["Z Bettouche, A Fischer - Bavarian Journal of Applied Sciences, 2023"],"snippet":"Transformer models have the ability to understand the meaning of text efficiently through the use of self-attention mechanisms. We investigate the bundled meanings in clusters of transformer-generated embeddings by evaluating the topical clustering …","url":["https://jas.bayern/index.php/bjas/article/download/135/55"]}
{"year":"2023","title":"Topological Interpretations of GPT-3","authors":["T Sun, B Nelson - arXiv preprint arXiv:2308.03565, 2023"],"snippet":"This is an experiential study of investigating a consistent method for deriving the correlation between sentence vector and semantic meaning of a sentence. We first used three state-of-the-art word/sentence embedding methods including GPT-3 …","url":["https://arxiv.org/pdf/2308.03565"]}
{"year":"2023","title":"TorchicTab: Semantic Table Annotation with Wikidata and Language Models","authors":["I Dasoulas, D Yang, X Duan, A Dimou - CEUR Workshop Proceedings, 2023"],"snippet":"… (3) The SOTAB Tables refer to the WDC Schema.org Table Annotation Benchmark3, generated by extracting Schema.org data from the Common Crawl. The data is grouped into separate tables for each class/host combination with the label spaces …","url":["https://lirias.kuleuven.be/retrieve/733695"]}
{"year":"2023","title":"TourismNLG: A Multi-lingual Generative Benchmark for the Tourism Domain","authors":["SM Bhatt, S Agarwal, O Gurjar, M Gupta, M Shrivastava - Advances in Information …, 2023"],"snippet":"… We use the mC4-pretrained mT5-base and CommonCrawl-pretrained mBART-large models, and perform domain adaptive pretraining to adapt them to the tourism domain. These are then further finetuned using task-specific labeled data. We …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28244-7_10"]}
{"year":"2023","title":"Toward automatic generation of control structures for process flow diagrams with large language models","authors":["E Hirtreiter, L Schulze Balhorn, AM Schweidtmann - AIChE Journal, 2023"],"snippet":"Developing Piping and Instrumentation Diagrams (P&IDs) is a crucial step during process development. We propose a data‐driven method for the prediction of control structures. Our methodology is inspired by end‐to‐end transformer‐based human …","url":["https://aiche.onlinelibrary.wiley.com/doi/pdf/10.1002/aic.18259"]}
{"year":"2023","title":"Toward Detection of Arabic Cyberbullying on Online Social Networks using Arabic BERT Models","authors":["ME AlFarah, I Kamel, Z Al Aghbari - 2023 International Symposium on Networks …, 2023"],"snippet":"Cyberbullying is one of the serious threats on social networks particularly toward children and teenagers. Cyberbullying can cause many harmful consequences towards victims such as anxiety, depression and even suicide. This research studies …","url":["https://ieeexplore.ieee.org/abstract/document/10323808/"]}
{"year":"2023","title":"Toward Semi-supervised Transcription of NAKO+ ILSE: Influence of Auto-matic Speech Recognition Performance on Manual Transcription Effort","authors":["E Brauße, K Scheck, T Schultz"],"snippet":"… The best performance was achieved using flat start HMMGaussian Mixture Model initialization in acoustic modeling and an RNN-LM trained on the ILSE training text data with additional, semantically similar Common Crawl text data. The mismatch …","url":["https://csl.uni-bremen.de/cms/images/documents/publications/BrausseScheckSchultz_ITG23.pdf"]}
{"year":"2023","title":"Towards a Common Understanding of Contributing Factors for Cross-Lingual Transfer in Multilingual Language Models: A Review","authors":["F Philippy, S Guo, S Haddadan - arXiv preprint arXiv:2305.16768, 2023"],"snippet":"In recent years, pre-trained Multilingual Language Models (MLLMs) have shown a strong ability to transfer knowledge across different languages. However, given that the aspiration for such an ability has not been explicitly incorporated in the design of …","url":["https://arxiv.org/pdf/2305.16768"]}
{"year":"2023","title":"Towards Auditing Large Language Models: Improving Text-based Stereotype Detection","authors":["W Zekun, S Bulathwela, AS Koshiyama - arXiv preprint arXiv:2311.14126, 2023"],"snippet":"… However, they show fairness concerns due to their training on extensive, unfiltered datasets such as book [8] and Wikipedia corpora [9], and large internet corpora like Common Crawl [10]. This training data often exhibits systemic biases …","url":["https://arxiv.org/pdf/2311.14126"]}
{"year":"2023","title":"Towards Automatic Evaluation of NLG Tasks Using Conversational Large Language Models","authors":["M Riyadh, MO Shafiq - Artificial Intelligence Applications and Innovations: 19th …, 2023"],"snippet":"Evaluating the quality of machine generated open-ended texts is a long-standing challenge in Natural Language Processing (NLP). Even though there have been dramatic advancements in the machine learning technologies that propelled the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-34107-6_34"]}
{"year":"2023","title":"Towards Automatic Identification of Violation Symptoms of Architecture Erosion","authors":["R Li, P Liang, P Avgeriou - arXiv preprint arXiv:2306.08616, 2023"],"snippet":"… Based on the fastText model, Meta published pre-trained word vectors with 300 dimensions for 157 languages constructed on Common Crawl and Wikipedia5. In this study, we employed the pre-trained fastText model, which can be transformed …","url":["https://arxiv.org/pdf/2306.08616"]}
{"year":"2023","title":"Towards Better Evaluation of Instruction-Following: A Case-Study in Summarization","authors":["O Skopek, R Aralikatte, S Gooding, V Carbune - arXiv preprint arXiv:2310.08394, 2023"],"snippet":"Despite recent advances, evaluating how well large language models (LLMs) follow user instructions remains an open problem. While evaluation methods of language models have seen a rise in prompt-based approaches, limited work on the …","url":["https://arxiv.org/pdf/2310.08394"]}
{"year":"2023","title":"Towards Comparable Active Learning","authors":["T Werner, J Burchert, L Schmidt-Thieme - arXiv preprint arXiv:2311.18356, 2023"],"snippet":"Active Learning has received significant attention in the field of machine learning for its potential in selecting the most informative samples for labeling, thereby reducing data annotation costs. However, we show that the reported lifts in recent literature …","url":["https://arxiv.org/pdf/2311.18356"]}
{"year":"2023","title":"Towards End-User Development for IoT: A Case Study on Semantic Parsing of Cooking Recipes for Programming Kitchen Devices","authors":["F Ventirozos, S Clinch, R Batista-Navarro - arXiv preprint arXiv:2309.14165, 2023"],"snippet":"Semantic parsing of user-generated instructional text, in the way of enabling end-users to program the Internet of Things (IoT), is an underexplored area. In this study, we provide a unique annotated corpus which aims to support the transformation of …","url":["https://arxiv.org/pdf/2309.14165"]}
{"year":"2023","title":"Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning","authors":["Z Charles, N Mitchell, K Pillutla, M Reneer, Z Garrett - arXiv preprint arXiv:2307.09619, 2023"],"snippet":"We introduce a library, Dataset Grouper, to create large-scale group-structured (eg, federated) datasets, enabling federated learning simulation at the scale of foundation models. This library allows the creation of group-structured versions of …","url":["https://arxiv.org/pdf/2307.09619"]}
{"year":"2023","title":"Towards General Text Embeddings with Multi-stage Contrastive Learning","authors":["Z Li, X Zhang, Y Zhang, D Long, P Xie, M Zhang - arXiv preprint arXiv:2308.03281, 2023"],"snippet":"We present GTE, a general-purpose text embedding model trained with multi-stage contrastive learning. In line with recent advancements in unifying various NLP tasks into a single format, we train a unified text embedding model by employing …","url":["https://arxiv.org/pdf/2308.03281"]}
{"year":"2023","title":"Towards Informed Pre-Training for Critical Error Detection in English-German","authors":["L Pucknat, M Pielka, R Sifa - 2022"],"snippet":"This paper presents two data augmentation methods for pre-training, to find critical errors in machine translations. This includes an alignment approach used in traditional machine translation and an imitation method, mimicking the structure of …","url":["https://ceur-ws.org/Vol-3341/KDML-LWDA_2022_CRC_9736.pdf"]}
{"year":"2023","title":"Towards Massively Multi-domain Multilingual Readability Assessment","authors":["T Naous, MJ Ryan, M Chandra, W Xu - arXiv preprint arXiv:2305.14463, 2023"],"snippet":"We present ReadMe++, a massively multi-domain multilingual dataset for automatic readability assessment. Prior work on readability assessment has been mostly restricted to the English language and one or two text domains. Additionally, the …","url":["https://arxiv.org/pdf/2305.14463"]}
{"year":"2023","title":"Towards Multilingual Automatic Dialogue Evaluation","authors":["J Mendonça, A Lavie, I Trancoso - arXiv preprint arXiv:2308.16795, 2023"],"snippet":"The main limiting factor in the development of robust multilingual dialogue evaluation metrics is the lack of multilingual data and the limited availability of open sourced multilingual dialogue systems. In this work, we propose a workaround for …","url":["https://arxiv.org/pdf/2308.16795"]}
{"year":"2023","title":"Towards multilingual automatic open-domain dialogue evaluation","authors":["J Mendonça, A Lavie, I Trancoso - Proceedings of the 24th Meeting of the Special …, 2023"],"snippet":"The main limiting factor in the development of robust multilingual open-domain dialogue evaluation metrics is the lack of multilingual data and the limited availability of open-sourced multilingual dialogue systems. In this work, we propose a …","url":["https://aclanthology.org/2023.sigdial-1.11.pdf"]}
{"year":"2023","title":"Towards Scalable Structured Data from Clinical Text","authors":["M Agrawal - 2023"],"snippet":"The adoption of electronic health records (EHRs) presents an incredible opportunity to improve medicine both at the point-of-care and through retrospective research. Unfortunately, many pertinent variables are trapped in unstructured clinical note text …","url":["https://dspace.mit.edu/bitstream/handle/1721.1/150049/Agrawal-magrawal-PhD-EECS-2023-thesis.pdf?sequence=1&isAllowed=y"]}
{"year":"2023","title":"Towards Sentence-level Text Readability Assessment for French","authors":["D Van Ngo, Y Parmentier - Second Workshop on Text Simplification, Accessibility …, 2023"],"snippet":"In this paper, we report on some experiments aimed at exploring the relation between document-level and sentence-level readability assessment for French. These were run on an open-source tailored corpus, which was automatically created …","url":["https://hal.science/hal-04192063/document"]}
{"year":"2023","title":"Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasets","authors":["R Tarbell, KKR Choo, G Dietrich, A Rios - arXiv preprint arXiv:2303.12898, 2023"],"snippet":"… To train T5, Google used a diverse corpus of text data from sources such as Wikipedia, Common Crawl, and the web pages crawled by Google. We apply the T5 model to the medical text-to-SQL task. The input to the model includes the database …","url":["https://arxiv.org/pdf/2303.12898"]}
{"year":"2023","title":"Toxic Content Recognition in Conversational Systems","authors":["A Černý - 2023"],"snippet":"Guidelines: The goal of the thesis is to devise a method of recognition of toxic content in conversational systems. 1) Review the current methods used for recognizing toxic content, with focus on methods based on embedding clustering …","url":["https://dspace.cvut.cz/bitstream/handle/10467/109402/F3-BP-2023-Cerny-Adam-toxic_content_recognition_in_conversational_systems.pdf"]}
{"year":"2023","title":"Traces of Human Attitudes in Contemporary and Historical Word Embeddings (1800-2000)","authors":["K Morehouse, V Rouduri, W Cunningham… - 2023"],"snippet":"… When inspecting the 36 separate models (each measuring the relationship between implicit attitudes and an evaluative language representation eg, Glove:Common Crawl WEAT-long), results showed that > 95% of the posterior fell outside the ROPE …","url":["https://www.researchsquare.com/article/rs-2922677/latest"]}
{"year":"2023","title":"Tracking the Newsworthiness of Public Documents","authors":["A Spangher, E Ferrara, B Welsh, N Peng, S Tumgoren… - arXiv preprint arXiv …, 2023"],"snippet":"… 2013–2023 and via the Common Crawl4. We parse article text5 and deduplicate based on text, and ultimately are left with a set of 202,644 SFChron articles6. We also scrape the public meeting calendar on the SFBOS website7 to collect all …","url":["https://arxiv.org/pdf/2311.09734"]}
{"year":"2023","title":"Tracking User Web Browsing Behavior: Privacy Harms and Security Benefits","authors":["K Crichton - 2023"],"snippet":"The presence of web tracking technology has grown to a near-ubiquitous state as web pages contain a growing number of trackers, representing progressively more and more third parties, that employ an increasingly diverse set of tracking techniques …","url":["https://search.proquest.com/openview/6b098df0b4bbe2dc898f1ba71c4d5c4c/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"TrackSign-labeled web tracking dataset","authors":["I Castell-Uroz, P Barlet-Ros - Computer Networks, 2023"],"snippet":"Recent studies [8] show that more than 95% of the websites available on the Internet contain at least one of the so-called web tracking systems. These systems are specialized in identifying their users by means of a plethora of different methods …","url":["https://www.sciencedirect.com/science/article/pii/S1389128623001329"]}
{"year":"2023","title":"Training CLIP models on Data from Scientific Papers","authors":["C Metzger - arXiv preprint arXiv:2311.04711, 2023"],"snippet":"Contrastive Language-Image Pretraining (CLIP) models are able to capture the semantic relationship of images and texts and have enabled a wide range of applications, from image retrieval to classification. These models are trained with …","url":["https://arxiv.org/pdf/2311.04711"]}
{"year":"2023","title":"Transfer Learning across Several Centuries: Machine and Historian Integrated Method to Decipher Royal Secretary's Diary","authors":["SL Kim, T Jang, J Ahn, H Lee, J Lee - arXiv preprint arXiv:2306.14592, 2023"],"snippet":"A named entity recognition and classification plays the first and foremost important role in capturing semantics in data and anchoring in translation as well as downstream study for history. However, NER in historical text has faced challenges …","url":["https://arxiv.org/pdf/2306.14592"]}
{"year":"2023","title":"Transfer Learning for Code-Mixed Data: Do Pretraining Languages Matter?","authors":["K Tatariya, H Lent, M De Lhoneux - Proceedings of the 13th Workshop on …, 2023"],"snippet":"… 2020) is the multilingual version of RoBERTa, pretrained on 100 languages from the CommonCrawl corpus. The Hindi included in the pretraining is … , with data sourced from the BBC news and the Common Crawl Corpus. It is trained with the …","url":["https://aclanthology.org/2023.wassa-1.32.pdf"]}
{"year":"2023","title":"Transfer Learning of Transformer-based Speech Recognition Models from Czech to Slovak","authors":["J Lehečka, JV Psutka, J Psutka - arXiv preprint arXiv:2306.04399, 2023"],"snippet":"… As training data, we used web pages from the Common Crawl project3. We downloaded and processed 34 crawls from August 2018 to October 2021 following the same cleaning and deduplicating rules as in the English C4 dataset [14] …","url":["https://arxiv.org/pdf/2306.04399"]}
{"year":"2023","title":"Transformer based Answer-Aware Bengali Question Generation","authors":["JF Ruma, TT Mayeesha, RM Rahman - International Journal of Cognitive Computing …, 2023"],"snippet":"… or T5 (Raffel et al., 2020) trained on a Common-Crawl based dataset called mC4 covering 101 languages. T5 model was introduced during … MC4 dataset contains 101 language variants drawn from the Common Crawl web scrape. MT5 did not …","url":["https://www.sciencedirect.com/science/article/pii/S2666307423000311"]}
{"year":"2023","title":"Transformer Based Image-Text Consistency Analysis for Infographic Articles","authors":["Y Chen, MC Chang - 2023 IEEE 6th International Conference on Multimedia …, 2023"],"snippet":"… We start with a T5 model that is pre-trained on both the common crawl-based dataset of Colossal Clean Crawled Corpus (C4) [8] and the Multi-NLI [13] datasets. Thereafter, we fine-tuned the Transformer further by using the Stanford Natural …","url":["https://ieeexplore.ieee.org/abstract/document/10254411/"]}
{"year":"2023","title":"Transformer Based Implementation for Automatic Book Summarization","authors":["S Porwal, L Bewoor, V Deshpande - International Journal of Intelligent Systems and …, 2022"],"snippet":"Document Summarization is the procedure of generating a meaningful and concise summary of a given document with the inclusion of relevant and topic-important points. There are two approaches-one is picking up the most relevant statements …","url":["https://ijisae.org/index.php/IJISAE/article/download/2421/1003"]}
{"year":"2023","title":"Transformer Models for Machine Translation and Streaming Automatic Speech Recognition","authors":["P Baquero Arnal - 2023"],"snippet":"[EN] Natural language processing (NLP) is a set of fundamental computing problems with immense applicability, as language is the natural communication vehicle for people. NLP, along with many other computer technologies, has been …","url":["https://riunet.upv.es/bitstream/handle/10251/193680/Baquero%20-%20Transformer%20models%20for%20Machine%20Translation%20and%20Streaming%20Automatic%20Speech%20Recognition.pdf?sequence=4"]}
{"year":"2023","title":"Transformer models for mining intents and predicting activities from emails in knowledge-intensive processes","authors":["F Khandaker, A Senderovich, J Zhao, E Cohen, E Yu… - Engineering Applications of …, 2024"],"snippet":"Process mining is an interdisciplinary field that combines Artificial Intelligence and Business Process Management to extract insights from historical event data. Knowledge-intensive processes, which predominantly involve knowledge work, are …","url":["https://www.sciencedirect.com/science/article/pii/S0952197623016342"]}
{"year":"2023","title":"Transformer models: an introduction and catalog","authors":["X Amatriain - arXiv preprint arXiv:2302.07730, 2023"],"snippet":"In the past few years we have seen the meteoric appearance of dozens of models of the Transformer family, all of which have funny, but not self-explanatory, names. The goal of this paper is to offer a somewhat comprehensive but simple catalog and …","url":["https://arxiv.org/pdf/2302.07730"]}
{"year":"2023","title":"Transformers in Healthcare: A Survey","authors":["S Nerella, S Bandyopadhyay, J Zhang, M Contreras… - arXiv preprint arXiv …, 2023"],"snippet":"With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications. Transformer is a type of deep learning …","url":["https://arxiv.org/pdf/2307.00067"]}
{"year":"2023","title":"Translating Ancient Chinese to Modern Chinese at Scale: A Large Language Model-based Approach","authors":["J Cao, D Peng, Y Shi, Z Jiang, L Jin - These articles are licensed under a Creative …, 2023"],"snippet":"Recently, the emergence of large language models (LLMs) has provided powerful foundation models for a wide range of natural language processing (NLP) tasks. However, the vast majority of the pre-training corpus for most existing LLMs is in …","url":["https://files.sciconf.cn/upload/file/20230830/20230830181020_39986.pdf#page=71"]}
{"year":"2023","title":"Trigger Warning Assignment as a Multi-Label Document Classification Problem","authors":["M Wiegmann, M Wolska, C Schröder, O Borchardt…"],"snippet":"A trigger warning is used to warn people about potentially disturbing content. We introduce trigger warning assignment as a multi-label classification task, create the Webis Trigger Warning Corpus 2022, and with it the first dataset of 1 million …","url":["https://webis.de/downloads/publications/papers/wiegmann_2023a.pdf"]}
{"year":"2023","title":"Triple-Entry Accounting as a Means of Auditing Large Language Models","authors":["K Sgantzos, MA Hemairy, P Tzavaras, S Stelios - Journal of Risk and Financial …, 2023"],"snippet":"The usage of Large Language Models (LMMs) and their exponential progress has created a Cambrian Explosion in the development of new tools for almost every field of science and technology, but also presented significant concerns regarding the AI …","url":["https://www.mdpi.com/1911-8074/16/9/383/pdf"]}
{"year":"2023","title":"Trustworthy Digital Repository Certification: A Longitudinal Study","authors":["DR Donaldson, SV Russell - Information for a Better World: Normality, Virtuality …, 2023"],"snippet":"Increasingly, government policies are directing federal agencies to make the results of federally funded scientific research publicly available in data repositories. Additionally, academic journal policies are progressively recommending that …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28032-0_42"]}
{"year":"2023","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Model","authors":["SN Hari, M Thomson - arXiv preprint arXiv:2308.11601, 2023"],"snippet":"… Language models are trained on data sampled from both generalized data sources like CommonCrawl as well as domain specific data (Pile sub-sets, financial data, clinical data), and also trained and fined tuned using different paradigms (Masked …","url":["https://arxiv.org/pdf/2308.11601"]}
{"year":"2023","title":"Tsetlin Machine for Fake News Detection: Enhancing Accuracy and Reliability","authors":["BV Ledaal - 2023"],"snippet":"This thesis aims to improve the accuracy of fake news detection by using Tsetlin Machines (TM). TMs are well suited for noisy and complex relations within the provided data, which on initial analysis, overlaps nicely with characteristics found in …","url":["https://uia.brage.unit.no/uia-xmlui/bitstream/handle/11250/3080494/no.uia:inspera:145679742:6941642.pdf?sequence=1"]}
{"year":"2023","title":"Tsinghua Issue-Generative AI, Learning And New Literacies","authors":["SY Chen - Journal of Educational Technology Development and …, 2023"],"snippet":"Launched in November 2022, OpenAI's ChatGPT garnered over 100 million users within two months, sparking a surge in research and concern over potential risks of extensive AI experiments. The article, originating from a conference presentation by …","url":["https://aquila.usm.edu/cgi/viewcontent.cgi?article=1205&context=jetde"]}
{"year":"2023","title":"TTIC's Submission to WMT-SLT 23","authors":["M Sandoval-Castañeda, Y Li, B Shi, D Brentari… - Proceedings of the Eighth …, 2023"],"snippet":"… on the German Colossal Cleaned Common Crawl (GC4) corpus, which is a cleaned and pre-processed Germanonly corpus based on Common Crawl. We take pre-… This is a subset of Common Crawl where the primary language is German …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.35.pdf"]}
{"year":"2023","title":"TUDublin at CheckThat! 2023: ChatGPT for Data Augmentation","authors":["E Shushkevich, J Cardiff - 2023"],"snippet":"This work describes the approach of the TUDublin team at the CheckThat! 2023 Task 2: Subjectivity in News Articles. This task is aimed to discern whether a sentence in a news article conveys the subjective perspective of its author or …","url":["https://www.dei.unipd.it/~faggioli/temp/CLEF2023-proceedings/paper-041.pdf"]}
{"year":"2023","title":"TunBERT: Pretraining BERT for Tunisian Dialect Understanding","authors":["H Haddad, AC Rouhou, A Messaoudi, A Korched… - SN Computer Science, 2023"],"snippet":"… We describe the process of creating a training dataset from collecting a Common-Crawl-based dataset, filtering and pre-processing the … Our models results indicate that a proportionately small sized Common-Crawl-based dataset (500K sentences, 67.2MB) …","url":["https://link.springer.com/article/10.1007/s42979-022-01541-y"]}
{"year":"2023","title":"TurkishBERTweet: Fast and Reliable Large Language Model for Social Media Analysis","authors":["A Najafi, O Varol - arXiv preprint arXiv:2311.18063, 2023"],"snippet":"Turkish is one of the most popular languages in the world. Wide us of this language on social media platforms such as Twitter, Instagram, or Tiktok and strategic position of the country in the world politics makes it appealing for the social network …","url":["https://arxiv.org/pdf/2311.18063"]}
{"year":"2023","title":"TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations at Twitter","authors":["X Zhang, Y Malkov, O Florez, S Park, B McWilliams… - Proceedings of the 29th …, 2023"],"snippet":"… It is trained on over two terabytes of CommonCrawl data. … pre-training objectives, the vast majority of the work has focused on text-only training objectives applied to general domain corpora, eg, Wikipedia and CommonCrawl. In this paper, we …","url":["https://dl.acm.org/doi/abs/10.1145/3580305.3599921"]}
{"year":"2023","title":"TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter","authors":["Y Chen, J Zou - arXiv preprint arXiv:2306.08310, 2023"],"snippet":"… ArtBench features 60,000 high-quality, genre-annotated images of artwork spanning ten different art genres from the 14th century to the 21st century; and LAION encompasses CLIP-similarity-filtered image-text pairs sourced from the Common Crawl. …","url":["https://arxiv.org/pdf/2306.08310"]}
{"year":"2023","title":"Twitter Accounts Suggestion: Pipeline Technique SpaCy Entity Recognition","authors":["S Algamdi, A Albanyan, SK Shah, Z Tariq - … International Conference on Big Data (Big …, 2022"],"snippet":"Twitter Accounts Suggestion is concerned with recommending accounts for the users according to their tweet contents. Twitter contains a massive amount of data that can be useful for knowing each user’s preferences. This paper uses Named …","url":["https://ieeexplore.ieee.org/abstract/document/10020570/"]}
{"year":"2023","title":"Two Neural Models for Multilingual Grammatical Error Detection","authors":["P Le-Hong, TMH Nguyen - Swedish Language Technology Conference and …, 2023"],"snippet":"This paper presents two neural models for multilingual grammatical error detection and their results in the MultiGED-2023 shared task. The first model uses a simple, purely supervised character-based approach. The second model uses a large …","url":["https://ecp.ep.liu.se/index.php/sltc/article/download/681/587"]}
{"year":"2023","title":"Typhoon: Thai Large Language Models","authors":["K Pipatanakul, P Jirabovonvisut, P Manakul… - arXiv preprint arXiv …, 2023"],"snippet":"… of the Common Crawl data [13], making Thai the 26th rank in terms of size in Common Crawl. … the Oscar dataset extracted a single package of the Common Crawl (CC) data and MC4 only … (1) Scaling the Data: we initiate the process by …","url":["https://arxiv.org/pdf/2312.13951"]}
{"year":"2023","title":"UBERT22: Unsupervised Pre-training of BERT for Low Resource Urdu Language","authors":["B Tahir, MA Mehmood - 2022 16th International Conference on Open Source …, 2022"],"snippet":"Natural Language Understanding (NLU) tools have enabled the development of sophisticated and powerful Natural Language Processing (NLP) models. However, this progress is limited to English and European languages and low resource …","url":["https://ieeexplore.ieee.org/abstract/document/10016821/"]}
{"year":"2023","title":"UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis","authors":["D Hu, L Wei, Y Liu, W Zhou, S Hu - arXiv preprint arXiv:2306.01093, 2023"],"snippet":"… It is pre-trained on filtered CommonCrawl data containing 100 languages. We use xlm-roberta-base3 to initialize XLM-R. … It is trained on an aggregation of datasets from the BBC news website and Common Crawl. We use castorini/afriberta_large3 …","url":["https://arxiv.org/pdf/2306.01093"]}
{"year":"2023","title":"UD-MULTIGENRE–a UD-Based Dataset Enriched with Instance-Level Genre Annotations","authors":["V Danilova, S Stymne - Proceedings of the 3rd Workshop on Multi-lingual …, 2023"],"snippet":"Prior research on the impact of genre on crosslingual dependency parsing has suggested that genre is an important signal. However, these studies suffer from a scarcity of reliable data for multiple genres and languages. While Universal …","url":["https://aclanthology.org/2023.mrl-1.19.pdf"]}
{"year":"2023","title":"UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation","authors":["X Liang, S Song, S Niu, Z Li, F Xiong, B Tang, Z Wy… - arXiv preprint arXiv …, 2023"],"snippet":"… For example, the Chinese data incorporated in GPT’s training from the Common Crawl corpus comprises less than 5%4. Evaluations by Type. Given the categorization of news into four types, we can … 4https://commoncrawl.github.io/cc-crawl-statistics/plots/languages.html …","url":["https://arxiv.org/pdf/2311.15296"]}
{"year":"2023","title":"UM6P at SemEval-2023 Task 3: News genre classification based on transformers, graph convolution networks and number of sentences","authors":["H Alami, A Benlahbib, A El Mahdaouy, I Berrada - Proceedings of the The 17th …, 2023"],"snippet":"This paper presents our proposed method for english documents genre classification in the context of SemEval 2023 task 3, subtask 1. Our method use ensemble technique to combine four distinct models predictions: Longformer …","url":["https://aclanthology.org/2023.semeval-1.118.pdf"]}
{"year":"2023","title":"UMUTeam at SemEval-2023 Task 12: Ensemble Learning of LLMs applied to Sentiment Analysis for Low-resource African Languages","authors":["JA García-Díaz, C Caparros-Laiz, Á Almela… - Proceedings of the The 17th …, 2023"],"snippet":"These working notes summarize the participation of the UMUTeam in the SemEval 2023 shared task: AfriSenti, focused on Sentiment Analysis in several African languages. Two subtasks are proposed, one in which each language is considered …","url":["https://aclanthology.org/2023.semeval-1.38.pdf"]}
{"year":"2023","title":"Uncovering and Categorizing Social Biases in Text-to-SQL","authors":["Y Liu, Y Gao, Z Su, X Chen, E Ash, JG Lou - arXiv preprint arXiv:2305.16253, 2023"],"snippet":"Content Warning: This work contains examples that potentially implicate stereotypes, associations, and other harms that could be offensive to individuals in certain social groups.} Large pre-trained language models are acknowledged to carry social …","url":["https://arxiv.org/pdf/2305.16253"]}
{"year":"2023","title":"UNDERSTANDING AND MITIGATING THE LABEL NOISE IN PRE-TRAINING ON DOWNSTREAM TASKS","authors":["H Chen, J Wang, A Shah, R Tao, H Wei, X Xie… - arXiv preprint arXiv …, 2023"],"snippet":"Pre-training on large-scale datasets and then fine-tuning on downstream tasks have become a standard practice in deep learning. However, pre-training data often contain label noise that may adversely affect the generalization of the model. This …","url":["https://arxiv.org/pdf/2309.17002"]}
{"year":"2023","title":"Understanding Catastrophic Forgetting in Language Models via Implicit Inference","authors":["S Kotha, JM Springer, A Raghunathan - arXiv preprint arXiv:2309.10105, 2023"],"snippet":"Fine-tuning (via methods such as instruction-tuning or reinforcement learning from human feedback) is a crucial step in training language models to robustly carry out tasks of interest. However, we lack a systematic understanding of the effects of fine-tuning …","url":["https://arxiv.org/pdf/2309.10105"]}
{"year":"2023","title":"Understanding Finetuning for Factual Knowledge Extraction from Language Models","authors":["M Kazemi, S Mittal, D Ramachandran - arXiv preprint arXiv:2301.11293, 2023"],"snippet":"… Recently, Language Models (LMs) pre-trained on large corpora of web documents such as CommonCrawl1 have achieved impressive results on multiple NLP tasks. In their pioneering work, Petroni et al. (2019) showed that LMs also …","url":["https://arxiv.org/pdf/2301.11293"]}
{"year":"2023","title":"Understanding Multilingual Language Models: Training, Representation and Architecture","authors":["V Ravishankar - 2023"],"snippet":"The field of natural language processing has seen numerous advancements since its inception during the Cold War, when attempts were made to automate translating Russian text to English. The 2010s have been a particularly fertile decade, going by …","url":["https://www.duo.uio.no/bitstream/handle/10852/102833/PhD-Ravishankar-2023.pdf?sequence=1"]}
{"year":"2023","title":"Understanding the Effectiveness of Very Large Language Models on Dialog Evaluation","authors":["J Huynh, C Jiao, P Gupta, S Mehri, P Bajaj… - arXiv preprint arXiv …, 2023"],"snippet":"… TNLGv2 has not seen datasets explicitly categorized as having dialog, but elements of casual language may be included in the Common Crawl snapshots and other internet-based corpora. Symbols: means that the category is included and × …","url":["https://arxiv.org/pdf/2301.12004"]}
{"year":"2023","title":"Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations","authors":["V Chen, QV Liao, JW Vaughan, G Bansal - arXiv preprint arXiv:2301.07255, 2023"],"snippet":"… The AI system used in this task was trained on the BIOS dataset [23], which contains hundreds of thousands of online biographies from the CommonCrawl corpus. While the original dataset consisted individuals with 29 professions, we …","url":["https://arxiv.org/pdf/2301.07255"]}
{"year":"2023","title":"Understanding Website Privacy Policies—A Longitudinal Analysis Using Natural Language Processing","authors":["V Belcheva, T Ermakova, B Fabian - Information, 2023"],"snippet":"Privacy policies are the main method for informing Internet users of how their data are collected and shared. This study aims to analyze the deficiencies of privacy policies in terms of readability, vague statements, and the use of pacifying phrases …","url":["https://www.mdpi.com/2078-2489/14/11/622"]}
{"year":"2023","title":"UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning","authors":["A Masry, P Kavehzadeh, XL Do, E Hoque, S Joty - arXiv preprint arXiv:2305.14761, 2023"],"snippet":"Charts are very popular for analyzing data, visualizing key insights and answering complex reasoning questions about data. To facilitate chart-based data analysis using natural language, several downstream tasks have been introduced recently …","url":["https://arxiv.org/pdf/2305.14761"]}
{"year":"2023","title":"UniDoc: A Universal Large Multimodal Model for Simultaneous Text Detection, Recognition, Spotting and Understanding","authors":["H Feng, Z Wang, J Tang, J Lu, W Zhou, H Li, C Huang - arXiv preprint arXiv …, 2023"],"snippet":"… The data were collected from the “Common Crawl” dataset, a vast web corpus containing publicly available web page. We opt for PowerPoint files based on two primary considerations. On one hand, PowerPoint presentations are characterized …","url":["https://arxiv.org/pdf/2308.11592"]}
{"year":"2023","title":"Unifying Corroborative and Contributive Attributions in Large Language Models","authors":["T Worledge, JH Shen, N Meister, C Winston, C Guestrin - arXiv preprint arXiv …, 2023"],"snippet":"As businesses, products, and services spring up around large language models, the trustworthiness of these models hinges on the verifiability of their outputs. However, methods for explaining language model outputs largely fall across two distinct fields …","url":["https://arxiv.org/pdf/2311.12233"]}
{"year":"2023","title":"UniManc at NADI 2023 Shared Task: A Comparison of Various T5-based Models for Translating Arabic Dialectical Text to Modern Standard Arabic","authors":["A Khered, I Abdelhalim, N Abdelhalim, A Soliman… - Proceedings of ArabicNLP …, 2023"],"snippet":"This paper presents the methods we developed for the Nuanced Arabic Dialect Identification (NADI) 2023 shared task, specifically targeting the two subtasks focussed on sentence-level machine translation (MT) of text written in any of four …","url":["https://aclanthology.org/2023.arabicnlp-1.71.pdf"]}
{"year":"2023","title":"Universal Multimodal Representation for Language Understanding","authors":["Z Zhang, K Chen, R Wang, M Utiyama, E Sumita, Z Li… - IEEE Transactions on …, 2023"],"snippet":"Abstract Representation learning is the foundation of natural language processing (NLP). This work presents new methods to employ visual information as assistant signals to general NLP tasks. For each sentence, we first retrieve a flexible number of images …","url":["https://www.computer.org/csdl/journal/tp/5555/01/10005816/1JF3SmbCxbi"]}
{"year":"2023","title":"University of Pennsylvania Working Paper s in Linguistic s","authors":["N Markl"],"snippet":"As speech datasets used in sociolinguistic research increase in size, laborious and time-intensive manual orthographic transcription is a challenge, limiting the amount of (transcribed) data which can be analysed. In this paper, I discuss the use of (commercial) …","url":["https://www.pure.ed.ac.uk/ws/files/345647217/Commercial_Automatic_MARKL_DOA05082022_VOR.pdf"]}
{"year":"2023","title":"Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services","authors":["M Xu, H Du, D Niyato, J Kang, Z Xiong, S Mao, Z Han… - arXiv preprint arXiv …, 2023"],"snippet":"Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable and diverse data using AI algorithms creatively. This survey paper focuses on the deployment of AIGC …","url":["https://arxiv.org/pdf/2303.16129"]}
{"year":"2023","title":"Unlocking Model Insights: A Dataset for Automated Model Card Generation","authors":["S Singh, H Lodwal, H Malwat, R Thakur, M Singh - arXiv preprint arXiv:2309.12616, 2023"],"snippet":"… LLaMa is trained on trillions of tokens, using publicly available datasets such as C4, CommonCrawl, Github, Wikipedia, Gutenberg and … , Wikipedia, StackExchange, scientific knowledge bases, scientific and academic Common Crawl …","url":["https://arxiv.org/pdf/2309.12616"]}
{"year":"2023","title":"Unlocking the Potential of Electronic Health Records With Danish Clinical Language Models for Text Mining","authors":["JS Pedersen - 2023"],"snippet":"This PhD dissertation focuses on the development of language technology that can be used to extract clinical information from Danish electronic health records (EHRs). EHRs contain important health-related information that can be used to guide the …","url":["https://portal.findresearcher.sdu.dk/files/243589320/Reduced_Unlocking_the_Potential_of_Electronic_Health_Records_With_Danish_Clinical_Language_Models_for_Text_Mining.pdf"]}
{"year":"2023","title":"Unmaking AI Imagemaking: A Methodological Toolkit for Critical Investigation","authors":["L Munn, L Magee, V Arora - arXiv preprint arXiv:2307.09753, 2023"],"snippet":"… To create the dataset, developers drew on Common Crawl, an immense repository of web pages scraped from the internet over twelve years which is now petabytes in size. Developers identified all the image tags in each webpage along …","url":["https://arxiv.org/pdf/2307.09753"]}
{"year":"2023","title":"Unsupervised Anomaly Detection in Multi-Topic Short-Text Corpora","authors":["M Ait-Saada, M Nadif - Proceedings of the 17th Conference of the European …, 2023"],"snippet":"Unsupervised anomaly detection seeks to identify deviant data samples in a dataset without using labels and constitutes a challenging task, particularly when the majority class is heterogeneous. This paper addresses this topic for textual data and …","url":["https://aclanthology.org/2023.eacl-main.101.pdf"]}
{"year":"2023","title":"Unsupervised ASR via Cross-Lingual Pseudo-Labeling","authors":["T Likhomanenko, L Lugosch, R Collobert - arXiv preprint arXiv:2305.13330, 2023","VIACL PSEUDO-LABELING"],"snippet":"… For African languages, we use Kinyarwanda only as a source language (as text data are not available in the Common Crawl dataset), and Swahili and Hausa only as target languages (as they are low resource). Finally, to compare with wav2vec-U …","url":["https://arxiv.org/pdf/2305.13330","https://openreview.net/pdf?id=4lOWCkhr4g"]}
{"year":"2023","title":"Unsupervised Deep Representation Learning for Low-Resourced Languages and Applications","authors":["K Goswami"],"snippet":"Artificial intelligence and Natural Language Processing (NLP) are becoming integral parts of modern technologies and amenities starting from the adaptation of Amazon Alexa to automatic chatbots in different industries. Though earlier NLP algorithms …","url":["https://aran.library.nuigalway.ie/bitstream/handle/10379/17767/PhD_Writing_camera_ready.pdf?sequence=1"]}
{"year":"2023","title":"Unsupervised Story Discovery from Continuous News Streams via Scalable Thematic Embedding","authors":["S Yoon, D Lee, Y Zhang, J Han - arXiv preprint arXiv:2304.04099, 2023"],"snippet":"… WCEP [11] is a benchmark news data set collected from Wikipedia Current Event Portal and the Common Crawl archive. We used articles in the stories of at least 50 articles and published in 2018 and 2019 (ie, WCEP18 and WCEP19). For a …","url":["https://arxiv.org/pdf/2304.04099"]}
{"year":"2023","title":"Unsupervised Ultra-Fine Entity Typing with Distributionally Induced Word Senses","authors":["C Biemann"],"snippet":"The lack of annotated data is one of the challenging issues in an ultra-fine entity typing, which is the task to assign semantic types for a given entity mention. Hence, automatic type generation is receiving increased interest, typically to be used as …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2023-sevgilietal-ufet-aist.pdf"]}
{"year":"2023","title":"Unveiling Multilinguality in Transformer Models: Exploring Language Specificity in Feed-Forward Networks","authors":["S Bhattacharya, O Bojar - arXiv preprint arXiv:2310.15552, 2023"],"snippet":"… The model description of the XGLM model states that the model was trained on CommonCrawl data of various languages. CzEng heavily relies on various freely accessible web sources and a part of the data included in CzEng is also drawn from …","url":["https://arxiv.org/pdf/2310.15552"]}
{"year":"2023","title":"Unveiling the Black Box: Investigating the Interplay between AI Technologies, Explainability, and Legal Implications","authors":["C Erdoğanyılmaz, B Mengünoğul, M Balci - 2023 8th International Conference on …, 2023"],"snippet":"Discovering patterns is the process of understanding, while explainability refers to the ability to represent the discovered patterns in a way that the target audience can comprehend. If we adapt the relevant proposition to explainability in law, jurists …","url":["https://ieeexplore.ieee.org/abstract/document/10286653/"]}
{"year":"2023","title":"Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment","authors":["F Xu, J Zhang, C Gao, J Feng, Y Li - arXiv preprint arXiv:2312.11813, 2023"],"snippet":"… As claimed in open source models [159, 139, 8], most of the training corpus are from the public web text like common crawl project and only limited common data processing methods are applied due to the high-cost of handling the large volume …","url":["https://arxiv.org/pdf/2312.11813"]}
{"year":"2023","title":"Urdu paraphrase detection: A novel DNN-based implementation using a semi-automatically generated corpus","authors":["HR Iqbal, R Maqsood, AA Raza, SU Hassan - Natural Language Engineering, 2023"],"snippet":"Automatic paraphrase detection is the task of measuring the semantic overlap between two given texts. A major hurdle in the development and evaluation of paraphrase detection approaches, particularly for South Asian languages like Urdu …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/62AF020B1B9BD7DAAE4F7B6262E81CA6/S1351324923000189a.pdf/urdu_paraphrase_detection_a_novel_dnnbased_implementation_using_a_semiautomatically_generated_corpus.pdf"]}
{"year":"2023","title":"Use of Large Language Model for Cyberbullying Detection","authors":["B Ogunleye, B Dharmaraj - 2023"],"snippet":"… It was trained on 100 languages from 2.5TB of filtered common crawl data. The \"RoBERTa\" part in XLM-RoBERTa originates from the fact that it uses the identical training procedures as the monolingual RoBERTa model, with the Masked Language Model …","url":["https://www.preprints.org/manuscript/202306.1075/download/final_file"]}
{"year":"2023","title":"USE OF SCHEMA. ORG MICRO-MARKUP IN E-COMMERCE PROJECTS","authors":["O Belz - Three Seas Economic Journal, 2022"],"snippet":"… were removed (Common Crawl, 2022). Both scientists and practitioners are working with the obtained data sets of the Common Crawl project. … SOTAB is based on data from schema.org and Common Crawl. SOTAB has two annotation …","url":["http://baltijapublishing.lv/index.php/threeseas/article/download/1964/1973"]}
{"year":"2023","title":"User-defined Content Detection Framework","authors":["K Kim, S Cho, Y Lee"],"snippet":"This paper presents UCDF, a simple interactive framework for training a classifier that can detect user-defined content. User-defined content signifies texts that a user wants to detect. UCDF receives examples of user-defined content as queries to …","url":["https://internlp.github.io/documents/2022/papers/8.pdf"]}
{"year":"2023","title":"Using AI-based detectors to control AI-assisted plagiarism in ESL writing:“The Terminator Versus the Machines”","authors":["K Ibrahim - Language Testing in Asia, 2023"],"snippet":"The release of ChatGPT marked the beginning of a new era of AI-assisted plagiarism that disrupts traditional assessment practices in ESL composition. In the face of this challenge, educators are left with little guidance in controlling AI-assisted …","url":["https://languagetestingasia.springeropen.com/articles/10.1186/s40468-023-00260-2"]}
{"year":"2023","title":"Using AI-generated suggestions from ChatGPT to optimize clinical decision support","authors":["S Liu, AP Wright, BL Patterson, JP Wanderer, RW Turer… - Journal of the American …, 2023"],"snippet":"Objective To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. Methods We supplied summaries of CDS logic to …","url":["https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocad072/7136722"]}
{"year":"2023","title":"Using artificial intelligence in day-to-day practice","authors":["M FRADKIN","M Fradkin - 2023"],"snippet":"… Most of the data used for ChatGPT’s dataset come from the Common Crawl, a collection of over 12 years of raw webpage data, metadata, and text extracts from websites starting in 2008. It does not have access to medical journal articles or raw …","url":["https://search.proquest.com/openview/800783b95fd58bb2f24f7bdfa01f9cb3/1?pq-origsite=gscholar&cbl=34319","https://www.contemporarypediatrics.com/view/using-artificial-intelligence-in-day-to-day-practice"]}
{"year":"2023","title":"Using Automated Procedures to Score Written Essays in Persian: An Application of the Multilingual BERT System","authors":["T Firoozi - 2023"],"snippet":"The automated scoring of student essays is now recognized as a significant development in both the research and practice of educational testing. The majority of the published studies on automated essay scoring (AES) focus on outcomes in …","url":["https://era.library.ualberta.ca/items/4d29bb1c-7d95-49c7-885e-bc69d25cd951/download/46d81deb-d867-4828-88dd-d5a16eac2ef5"]}
{"year":"2023","title":"USING CHATGPT TO INVESTIGATE TRENDS IN DIGITAL STORYTELLING AND KNOWLEDGE SHARING IN HIGHER EDUCATION","authors":["D Cranfield, I Venter, A Daniels - EDULEARN23 Proceedings, 2023"],"snippet":"Literature reviews are traditionally used by researchers to consider large bodies of knowledge within their field of research and to synthesize new knowledge. The principal objective of this research was to do a state-of-the-art review using ChatGPT …","url":["https://library.iated.org/view/CRANFIELD2023USI"]}
{"year":"2023","title":"Using Domain-Specific Word Embeddings to Examine the Demand for Skills","authors":["S Chaturvedi, K Mahajan, Z Siddique - 2023"],"snippet":"… We examine and compare domain-specific word embeddings with word embeddings trained on Common Crawl on … Common Crawl on the web and Wikipedia demonstrates the benefits of using the former.As opposed to pre-trained …","url":["https://docs.iza.org/dp16593.pdf"]}
{"year":"2023","title":"Using Language Models to Detect Alarming Student Responses","authors":["CM Ormerod, M Patel, H Wang - arXiv preprint arXiv:2305.07709, 2023"],"snippet":"This article details the advances made to a system that uses artificial intelligence to identify alarming student responses. This system is built into our assessment platform to assess whether a student's response indicates they are a threat to …","url":["https://arxiv.org/pdf/2305.07709"]}
{"year":"2023","title":"Using Large Pre-Trained Language Model to Assist FDA in Premarket Medical Device Classification","authors":["Z Xu - SoutheastCon 2023, 2023"],"snippet":"… This paper selects the FastText embeddings with subword information pre-trained on Common Crawl which has a dimension of 300. When constructing the embeddings for the device descriptions, pre-trained embeddings are found for each …","url":["https://ieeexplore.ieee.org/abstract/document/10115070/"]}
{"year":"2023","title":"Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour …","authors":["R West, F Bonin, J Thomas, AJ Wright… - 2023"],"snippet":"… The vectors are generated based on the cooccurrence statistics of words in a large corpus of text, such as Wikipedia or Common Crawl. The algorithm is trained to learn a weighted average of the co-occurrence probabilities between words …","url":["https://psyarxiv.com/wzn2b/download"]}
{"year":"2023","title":"Using the web to explain claims","authors":["N Bremen - 2023"],"snippet":"An important part of human interaction is argumentation. Arguments can be found anywhere and have been studied in various disciplines, going all the way back to ancient times. With the rise of the world wide web, and more specifically the social …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/43676/2023-02-13%20Thesis%20Nick%20van%20Bremen.pdf?sequence=1"]}
{"year":"2023","title":"Using Transformers to Extract Date Expressions From Receipts","authors":["A Leander"],"snippet":"The extraction of date expressions in documents is a time-consuming task if done manually. For computers, automating this process can be achieved through various methods. In this thesis, I compare a regular expression system that extracts date …","url":["https://lup.lub.lu.se/student-papers/record/9138650/file/9138651.pdf"]}
{"year":"2023","title":"Using Vector Embeddings and Feature Vectors to Humor Identification","authors":["MC Aguirre-Delgado, AE Cadena-Bautista - 2023"],"snippet":"Expressing prejudice is the most common strategy to harm minority groups. Prejudice is defined as\" the formation of a negative concept or judgment in advance about members of a race, religion, or any other significant social group, despite facts …","url":["https://ceur-ws.org/Vol-3496/huhu-paper7.pdf"]}
{"year":"2023","title":"Using word embeddings to investigate human psychology: Methods and applications","authors":["HWS BAO, ZX WANG, X CHENG, Z SU, Y YANG… - Advances in Psychological …"],"snippet":"… 词向量通常是根据大 规模文本语料训练的(比如 Common Crawl 语料库 覆盖了多种 来源,万亿级规模的网页链接), 分析 结果更能代表人群总体.而传统方法中, 样本量 一般 比较有限, 且以学生样本居多, 只有经过严 格,系统的抽样才能保证样本代表性. 第三 …","url":["https://journal.psych.ac.cn/xlkxjz/EN/article/downloadArticleFile.do?attachType=PDF&id=6610"]}
{"year":"2023","title":"UT5: Pretraining Non autoregressive T5 with unrolled denoising","authors":["MG Salem, J Ye, CC Lin, F Liu - arXiv preprint arXiv:2311.08552, 2023"],"snippet":"… For our pretraining experiments, we use the C4 dataset, which is a large-scale web document corpus created by scraping the Common Crawl data. The C4 dataset contains over 750GB of text data and includes a diverse range of topics, such as …","url":["https://arxiv.org/pdf/2311.08552"]}
{"year":"2023","title":"Vacaspati: A Diverse Corpus of Bangla Literature","authors":["P Bhattacharyya, J Mondal, S Maji, A Bhattacharya - arXiv preprint arXiv:2307.05083, 2023"],"snippet":"Bangla (or Bengali) is the fifth most spoken language globally; yet, the state-of-the-art NLP in Bangla is lagging for even simple tasks such as lemmatization, POS tagging, etc. This is partly due to lack of a varied quality corpus. To alleviate this need, we …","url":["https://arxiv.org/pdf/2307.05083"]}
{"year":"2023","title":"Valence without meaning: investigating form and semantic components in pseudowords valence","authors":["D Gatti, L Raveling, A Petrenco, F Günther - 2023"],"snippet":"Valence is a dominant semantic dimension, and it is fundamentally linked to basic approach-avoidance behavior within a broad range of contexts. Previous studies have shown that it is possible to approximate the valence of existing words based on …","url":["https://psyarxiv.com/sfzgr/download?format=pdf"]}
{"year":"2023","title":"Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing","authors":["Z Wang, H Wang"],"snippet":"Existing regression models tend to fall short in both accuracy and uncertainty estimation when the label distribution is imbalanced. In this paper, we propose a probabilistic deep learning model, dubbed variational imbalanced regression (VIR) …","url":["http://www.wanghao.in/paper/NIPS23_VIR.pdf"]}
{"year":"2023","title":"Vashantor: A Large-scale Multilingual Benchmark Dataset for Automated Translation of Bangla Regional Dialects to Bangla Language","authors":["FTJ Faria, MB Moin, AA Wase, M Ahmmed, MR Sani… - arXiv preprint arXiv …, 2023"],"snippet":"The Bangla linguistic variety is a fascinating mix of regional dialects that adds to the cultural diversity of the Bangla-speaking community. Despite extensive study into translating Bangla to English, English to Bangla, and Banglish to Bangla in the past …","url":["https://arxiv.org/pdf/2311.11142"]}
{"year":"2023","title":"Vax-Culture: A Dataset for Studying Vaccine Discourse on Twitter","authors":["MR Zarei, M Christensen, S Everts, M Komeili - arXiv preprint arXiv:2304.06858, 2023"],"snippet":"Vaccine hesitancy continues to be a main challenge for public health officials during the COVID-19 pandemic. As this hesitancy undermines vaccine campaigns, many researchers have sought to identify its root causes, finding that the increasing …","url":["https://arxiv.org/pdf/2304.06858"]}
{"year":"2023","title":"VECO 2.0: Cross-lingual Language Model Pre-training with Multi-granularity Contrastive Learning","authors":["ZR Zhang, C Tan, S Huang, F Huang - arXiv preprint arXiv:2304.08205, 2023"],"snippet":"Recent studies have demonstrated the potential of cross-lingual transferability by training a unified Transformer encoder for multiple languages. In addition to involving the masked language model objective, existing cross-lingual pre-training …","url":["https://arxiv.org/pdf/2304.08205"]}
{"year":"2023","title":"Vega-mt: The jd explore academy machine translation system for wmt22","authors":["C Zan, K Peng, L Ding, B Qiu, B Liu, S He, Q Lu… - Proceedings of the Seventh …, 2022"],"snippet":"We describe the JD Explore Academy’s submission of the WMT 2022 shared general translation task. We participated in all high-resource tracks and one medium-resource track, including Chinese-English, German-English, Czech-English, Russian-English …","url":["https://aclanthology.org/2022.wmt-1.37.pdf"]}
{"year":"2023","title":"Verbalising Query Results to Text","authors":["MS Xydas - 2023"],"snippet":"… C4 is a colossal, cleaned version of Common Crawl’s web crawl corpus. It was based on Common Crawl dataset which consists of all the websites on the internet. In our case, C4 has a regulatory effect on our pretraining process and we use a …","url":["https://pergamos.lib.uoa.gr/uoa/dl/object/3336431/file.pdf"]}
{"year":"2023","title":"ViCGCN: Graph Convolutional Network with Contextualized Language Models for Social Media Mining in Vietnamese","authors":["CT Phan, QN Nguyen, CT Dang, TH Do, K Van Nguyen - arXiv preprint arXiv …, 2023"],"snippet":"… XLM-R particularly impressive is the extensive and careful curation of over 2.5TB of data from CommonCrawl. Among its notable contributions are the improvements made for low-resource languages through specialized training and vocabulary …","url":["https://arxiv.org/pdf/2309.02902"]}
{"year":"2023","title":"Video question answering supported by a multi-task learning objective","authors":["A Falcon, G Serra, O Lanz - Multimedia Tools and Applications, 2023"],"snippet":"… By using GloVe, pretrained on the Common Crawl dataset , a vector of size E = 300 is computed for each word in both question and answer. Since GloVe is not contextual, question and answer can be given in input to it either jointly or separately …","url":["https://link.springer.com/article/10.1007/s11042-023-14333-0"]}
{"year":"2023","title":"VideoCon: Robust Video-Language Alignment via Contrast Captions","authors":["H Bansal, Y Bitton, I Szpektor, KW Chang, A Grover - arXiv preprint arXiv:2311.10111, 2023"],"snippet":"Despite being (pre)trained on a massive amount of data, state-of-the-art video-language alignment models are not robust to semantically-plausible contrastive changes in the video captions. Our work addresses this by identifying a broad spectrum of …","url":["https://arxiv.org/pdf/2311.10111"]}
{"year":"2023","title":"Vision-Aware Language Reasoning for Referring Image Segmentation","authors":["F Xu, B Luo, C Zhang, L Xu, M Pu, B Li - Neural Processing Letters, 2023"],"snippet":"… Like [20, 28], we use the Glove word embedding [48] pretrained on Common Crawl 840B tokens as the language initial encoding. We default the length of expressions to 20 on all datasets and perform language feature extraction …","url":["https://link.springer.com/article/10.1007/s11063-023-11377-z"]}
{"year":"2023","title":"Vision-Language Models for Vision Tasks: A Survey","authors":["J Zhang, J Huang, S Jin, S Lu - arXiv preprint arXiv:2304.00685, 2023"],"snippet":"Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition …","url":["https://arxiv.org/pdf/2304.00685"]}
{"year":"2023","title":"ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing","authors":["QN Nguyen, TC Phan, DV Nguyen, K Van Nguyen - arXiv preprint arXiv:2310.11166, 2023"],"snippet":"English and Chinese, known as resource-rich languages, have witnessed the strong development of transformer-based language models for natural language processing tasks. Although Vietnam has approximately 100M people speaking …","url":["https://arxiv.org/pdf/2310.11166"]}
{"year":"2023","title":"Visual experience modulates the sensitivity to the distributional history of words in natural language","authors":["G Anceresi, D Gatti, M Marelli, T Vecchi, L Rinaldi - 2023"],"snippet":"Different experiential traces (ie, linguistic, motor and perceptual) are likely contributing to the organization of human semantic knowledge. Here, we aimed to address this issue by investigating whether visual experience may affect the …","url":["https://psyarxiv.com/jqa9k/download?format=pdf"]}
{"year":"2023","title":"Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature","authors":["ACAM de Faria, FC Bastos, JVNA da Silva, VL Fabris… - arXiv preprint arXiv …, 2023","CFG dos Sants, F de Castro Bastos, ACAM de Faria… - 2023"],"snippet":"… More technically, this new architecture has a language model based on Text-toText transformer and uses the base of T5 [78] because of its extensive pre-training data using Common Crawl, that is 750GB of cleaned English text data. To complement, a …","url":["https://arxiv.org/pdf/2305.11033","https://www.researchsquare.com/article/rs-3015858/latest.pdf"]}
{"year":"2023","title":"Visual-Semantic Learning","authors":["C Yin - 2023"],"snippet":"… of 15 words, while the questions with length smaller than 15 were padded with zeros to the length of 15 (10 for the MSVD-QA dataset), and each word in the questions was represented as a 300D vectors using the GloVe word embedding [214] …","url":["https://search.proquest.com/openview/f5cf7cabc3e1cbcb0a2fece160ce1319/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
{"year":"2023","title":"Visualisation and Classification of Phishing URL using Ensemble Learning Algorithms and Hyper-Parameter Tuning","authors":["G Agarwal, C Goel, K Jindal, T Subbulakshmi - 2023 Third International Conference …, 2023"],"snippet":"… Alexa and Common Crawl were used to gather legitimate URLs. Lexical features, host-based features, and correlated feature groups are the three categories used to classify the features. Lexical features are textual aspects of the URL rather than the …","url":["https://ieeexplore.ieee.org/abstract/document/10176642/"]}
{"year":"2023","title":"Vocabulary-free Image Classification","authors":["A Conti, E Fini, M Mancini, P Rota, Y Wang, E Ricci - arXiv preprint arXiv:2306.00917, 2023"],"snippet":"Recent advances in large vision-language models have revolutionized the image classification paradigm. Despite showing impressive zero-shot capabilities, a pre-defined set of categories, aka the vocabulary, is assumed at test time for composing the …","url":["https://arxiv.org/pdf/2306.00917"]}
{"year":"2023","title":"WADER at SemEval-2023 Task 9: A Weak-labelling framework for Data augmentation in tExt Regression Tasks","authors":["M Suri, A Garg, D Chaudhary, I Gorton, B Kumar - arXiv preprint arXiv:2303.02758, 2023"],"snippet":"… This model is pre-trained on a massive dataset of 2.5 terabytes of CommonCrawl data filtered for 100 different languages. By training on such a large and diverse dataset, XLM-RoBERTa is able to capture the linguistic nuances and patterns that …","url":["https://arxiv.org/pdf/2303.02758"]}
{"year":"2023","title":"WanJuan: A Comprehensive Multimodal Dataset for Advancing English and Chinese Large Models","authors":["C He, Z Jin, C Xu, J Qiu, B Wang, W Li, H Yan… - arXiv preprint arXiv …, 2023"],"snippet":"The rise in popularity of ChatGPT and GPT-4 has significantly accelerated the development of large models, leading to the creation of numerous impressive large language models(LLMs) and multimodal large language models (MLLMs). These …","url":["https://arxiv.org/pdf/2308.10755"]}
{"year":"2023","title":"WDC Products: A Multi-Dimensional Entity Matching Benchmark","authors":["R Peeters, RC Der, C Bizer - arXiv preprint arXiv:2301.09521, 2023"],"snippet":"… The first step of the pipeline is the extraction of large amounts of product offers from the Common Crawl4 using schema.org annotations. Some product offers contain product identifiers like MPNs and GTINs which allow us to group offers into …","url":["https://arxiv.org/pdf/2301.09521"]}
{"year":"2023","title":"Weak supervision and label noise handling for Natural language processing in low-resource scenarios","authors":["MA Hedderich - 2022"],"snippet":"The lack of large amounts of labeled data is a significant factor blocking many low-resource languages and domains from catching up with recent advancements in natural language processing. To reduce this dependency on labeled instances, weak …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/35026/1/MHedderich_Thesis_23-01-11.pdf"]}
{"year":"2023","title":"Web content classification analysis","authors":["TX Nissopoulou - 2023"],"snippet":"This dissertation was written as a part of the MSc in Data Science at the International Hellenic University. Web analytics is a way for companies to learn more about the people who visit their websites. This information may include things like how people …","url":["https://repository.ihu.edu.gr/xmlui/bitstream/handle/11544/30145/thesis.pdf?sequence=1"]}
{"year":"2023","title":"Web Page Prediction Model using Machine Learning Approaches: A Review","authors":["PA Omosebi, AP Adewole, O Sennaike - … on Science, Engineering and Business for …, 2023"],"snippet":"Webpage classification and prefetching are essential techniques to reduce internet access latency. However, insufficient server resources and network bandwidth can lead to inefficient usage when the majority of the prefetched web pages are not …","url":["https://ieeexplore.ieee.org/abstract/document/10124586/"]}
{"year":"2023","title":"Web Readability Challenges","authors":["E Elahi, AMI Maqueda, JLM Lara - Proceedings of the Computational Methods in …, 2023"],"snippet":"… The datasets called Common Crawl comprised more than sixty million domain names, seven million Word documents, and more than ninety million PDF documents. Around sixty percent of the information is created from the organization, commercial …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21438-7_35"]}
{"year":"2023","title":"Web Structure Mining and Social Network Analysis","authors":["C Bizer"],"snippet":"… Covers 3.5 billion web pages and 128 billion hyperlinks, extracted from Common Crawl 2012 …","url":["https://www.uni-mannheim.de/media/Einrichtungen/dws/Files_Teaching/Web_Mining/FSS2023/WM02-WebStructureMining-Part1-FSS2023.pdf"]}
{"year":"2023","title":"WebCPM: Interactive Web Search for Chinese Long-form Question Answering","authors":["Y Qin, Z Cai, D Jin, L Yan, S Liang, K Zhu, Y Lin, X Han… - arXiv preprint arXiv …, 2023"],"snippet":"… 2021) covers 101 languages collected from the public Common Crawl web scrape. mT5 achieves superior performance in various … Mengzi-T5 was trained on Chinese Wikipedia, Chinese News, and Common Crawl and the total size of the pre-training …","url":["https://arxiv.org/pdf/2305.06849"]}
{"year":"2023","title":"WEBIE: Faithful and Robust Information Extraction on the Web","authors":["C Whitehouse, C Vania, AF Aji, C Christodoulopoulos…"],"snippet":"… We present WEBIE, the first large-scale, entity-linked closed IE dataset consisting of 1.6M sentences automatically collected from the English Common Crawl corpus. WEBIE also includes negative examples, ie sentences without fact triples, to better …","url":["https://christos-c.com/papers/whitehouse_23_webie.pdf"]}
{"year":"2023","title":"wGMU: A Novel Fusion Strategy to Identify the Important Parts of Sentence for Relation Classification","authors":["D Escobar-Grisales, SA Moreno-Acevedo… - Workshop on Engineering …, 2023"],"snippet":"… This model was pre-trained with 2.5 TB of text data from the Common Crawl corpus [17], which includes text in 100 different languages. This extensive pre-training has allowed RoBERTa to compute text representations in multiple languages …","url":["https://link.springer.com/chapter/10.1007/978-3-031-46739-4_16"]}
{"year":"2023","title":"What can we learn from Data Leakage and Unlearning for Law?","authors":["J Borkar - arXiv preprint arXiv:2307.10476, 2023"],"snippet":"… the model with the start-of-the-sequence token (2) Prompting the model with random ten tokens from the Common Crawl3 for each … 5since we use tokens from common crawl for prompts we assume that the attacker has access to a dataset with …","url":["https://arxiv.org/pdf/2307.10476"]}
{"year":"2023","title":"What ChatGPT Tells Us about Gender: A Cautionary Tale about Performativity and Gender Biases in AI","authors":["N Gross - Social Sciences, 2023"],"snippet":"Large language models and generative AI, such as ChatGPT, have gained influence over people’s personal lives and work since their launch, and are expected to scale even further. While the promises of generative artificial intelligence are compelling …","url":["https://www.mdpi.com/2076-0760/12/8/435"]}
{"year":"2023","title":"What comes next?: Investigating the neural correlates of predictability during conversation with fMRI","authors":["J Sundström - 2023"],"snippet":"The notion that prediction plays a role in language processing is getting less controversial, however research and discussion is ongoing as to the nature and extent of its involvement. Previous studies have mainly focused on prediction during …","url":["https://www.diva-portal.org/smash/get/diva2:1768530/FULLTEXT01.pdf"]}
{"year":"2023","title":"What do text-to-image models know about the languages of the world?","authors":["V Firsanova - Записки научных семинаров ПОМИ, 2023"],"snippet":"… Another way is to use statistics of a large multilingual dataset such as Common Crawl [6]. We could try using statistics of the most spoken languages in the world [13]. But it would not be representative for our purposes because widespread spoken …","url":["https://www.mathnet.ru/rus/znsl7425"]}
{"year":"2023","title":"What is (and was) a person? Evidence on historical mind perceptions from natural language","authors":["E Ash, D Stammbach, K Tobia - Cognition, 2023"],"snippet":"… Embeddings trained on a broader, less-well-curated corpus (Common Crawl) get worse performance in the human validation. Performance with our newly trained embeddings using recent decades of the Corpus of Historical American English (Davies …","url":["https://www.sciencedirect.com/science/article/pii/S001002772300135X"]}
{"year":"2023","title":"What is a Fair Diffusion Model? Designing Generative Text-To-Image Models to Incorporate Various Worldviews","authors":["Z De Simone, A Boggust, A Satyanarayan, A Wilson - arXiv preprint arXiv:2309.09944, 2023"],"snippet":"… For example, Stable Diffusion [37] is trained on the image-text pairs from LAION-5B [41], a dataset synthesized from a repository of webcrawled data (Common Crawl [17]) and filtered using a CLIP [35] image classification model. This data represents a …","url":["https://arxiv.org/pdf/2309.09944"]}
{"year":"2023","title":"What Makes ImageNet Look Unlike LAION","authors":["A Shirali, M Hardt - arXiv preprint arXiv:2306.15769, 2023"],"snippet":"ImageNet was famously created from Flickr image search results. What if we recreated ImageNet instead by searching the massive LAION dataset based on image captions alone? In this work, we carry out this counterfactual investigation …","url":["https://arxiv.org/pdf/2306.15769"]}
{"year":"2023","title":"What Makes LLMs Large?","authors":["T Amaratunga - … Large Language Models: Learning Their Underlying …, 2023"],"snippet":"By now you should have a high-level understanding of the concepts of natural language processing and how the transformer architecture and attention mechanisms revolutionized the NLP field and how it changed the way we look at …","url":["https://link.springer.com/chapter/10.1007/979-8-8688-0017-7_4"]}
{"year":"2023","title":"WHAT MAKES PRE-TRAINED VISUAL REPRESENTATIONS SUCCESSFUL FOR ROBUST MANIPULATION?","authors":["K Burns, Z Witzel, JI Hamid, T Yu, C Finn, K Hausman"],"snippet":"Inspired by the success of transfer learning in computer vision, roboticists have investigated visual pre-training as a means to improve the learning efficiency and generalization ability of policies learned from pixels. To that end, past work has …","url":["https://kayburns.github.io/segmentingfeatures/static/segmentingfeatures_paper.pdf"]}
{"year":"2023","title":"What Works When in Context-aware Neural Machine Translation?","authors":["H Gete, T Etchegoyhen, G Labaka - Proceedings of the 24th Annual Conference of …, 2023"],"snippet":"Document-level Machine Translation has emerged as a promising means to enhance automated translation quality, but it is currently unclear how effectively context-aware models use the available context during translation. This paper aims …","url":["https://aclanthology.org/2023.eamt-1.15.pdf"]}
{"year":"2023","title":"What's in a Name? Evaluating Assembly-Part Semantic Knowledge in Language Models through User-Provided Names in CAD Files","authors":["P Meltzer, JG Lambourne, D Grandi - arXiv preprint arXiv:2304.14275, 2023"],"snippet":"Semantic knowledge of part-part and part-whole relationships in assemblies is useful for a variety of tasks from searching design repositories to the construction of engineering knowledge bases. In this work we propose that the natural language …","url":["https://arxiv.org/pdf/2304.14275"]}
{"year":"2023","title":"What's in a Name? Evaluating Assembly-Part Semantic Knowledge in Language Models Through User-Provided Names in Computer Aided Design Files","authors":["P Meltzer, JG Lambourne, D Grandi - Journal of Computing and Information Science …, 2024"],"snippet":"Semantic knowledge of part-part and part-whole relationships in assemblies is useful for a variety of tasks from searching design repositories to the construction of engineering knowledge bases. In this work, we propose that the natural language …","url":["https://asmedigitalcollection.asme.org/computingengineering/article/24/1/011002/1163204"]}
{"year":"2023","title":"What's In My Big Data?","authors":["Y Elazar, A Bhagia, I Magnusson, A Ravichander… - arXiv preprint arXiv …, 2023"],"snippet":"… The dataset: The Colossal Clean Crawled Corpus (C4 in short) is based on Common Crawl as a source of text that was scraped from the … We use the latest version (v.3.1.0) which was used to train umT5, containing documents collected from …","url":["https://arxiv.org/pdf/2310.20707"]}
{"year":"2023","title":"What's in the News? Towards Identification of Bias by Commission, Omission, and Source Selection (COSS)","authors":["A Zhukova, TL Ruas, F Hamborg, K Donnay, B Gipp - 2023"],"snippet":"In a world overwhelmed with news, determining which information comes from reliable sources or how neutral is the reported information in the news articles poses a challenge to news readers. In this paper, we propose a methodology for …","url":["https://www.gipp.com/wp-content/papercite-data/pdf/zhukova2023.pdf"]}
{"year":"2023","title":"When AI Moves Downstream","authors":["F Grodzinsky, K Miller, M Wolf - International Conference on Computer Ethics, 2023"],"snippet":"… The training set for GPT-3 filtered a version of Common Crawl used to develop GPT-2. These were deliberate developer choices. In … Developers should be aware of the harm that uncurated and unanalyzed large data sets gathered from web …","url":["http://journals.library.iit.edu/index.php/CEPE2023/article/download/245/250"]}
{"year":"2023","title":"When Automated Assessment Meets Automated Content Generation: Examining Text Quality in the Era of GPTs","authors":["M Bevilacqua, K Oketch, R Qin, W Stamey, X Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"… RoBERTa also uses BookCorpus and Wikipedia, but in addition to common crawl news (CC-News), open web text, and stories, resulting in over 30 million tokens used for pre-training [50]. Both BERT and RoBERTa have performed well on text …","url":["https://arxiv.org/pdf/2309.14488"]}
{"year":"2023","title":"When Giant Language Brains Just Aren't Enough! Domain Pizzazz with Knowledge Sparkle Dust","authors":["MT Nguyen, DH Nguyen, S Sabahi, H Le, J Yang… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs) have significantly advanced the field of natural language processing, with GPT models at the forefront. While their remarkable performance spans a range of tasks, adapting LLMs for real-world business …","url":["https://arxiv.org/pdf/2305.07230"]}
{"year":"2023","title":"When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities","authors":["J Chen, Z Liu, X Huang, C Wu, Q Liu, G Jiang, Y Pu… - arXiv preprint arXiv …, 2023"],"snippet":"… For another thing, the pre-training is conducted based on much more unsupervised corpora, with hundreds of billions or trillions of tokens carefully filtered from sources like Common Crawl, GitHub, Wikipedia, Books, ArXiv, etc. The impact …","url":["https://arxiv.org/pdf/2307.16376"]}
{"year":"2023","title":"When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale","authors":["M Marion, A Üstün, L Pozzobon, A Wang, M Fadaee… - arXiv preprint arXiv …, 2023"],"snippet":"… test set from the same CommonCrawl snapshot with identical … CommonCrawl A reference model trained on Wikipedia (an example of a clean noise-free corpus) achieves consistently lower validation perplexity compared to a reference model …","url":["https://arxiv.org/pdf/2309.04564"]}
{"year":"2023","title":"When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming","authors":["H Mozannar, G Bansal, A Fourney, E Horvitz - arXiv preprint arXiv:2306.04930, 2023"],"snippet":"AI powered code-recommendation systems, such as Copilot and CodeWhisperer, provide code suggestions inside a programmer's environment (eg, an IDE) with the aim to improve their productivity. Since, in these scenarios, programmers accept and …","url":["https://arxiv.org/pdf/2306.04930"]}
{"year":"2023","title":"Where Did the News Come From? Detection of News Agency Releases in Historical Newspapers","authors":["L Marxen - 2023"],"snippet":"Since their beginnings in the 1830s and 1840s, news agencies have played an important role in the national and international news market, aiming to deliver news as fast and as reliable as possible. While we know that newspapers have been …","url":["https://infoscience.epfl.ch/record/305129/files/Marxen_Master_Thesis_2023_08_18.pdf"]}
{"year":"2023","title":"Where's the Liability in Harmful AI Speech?","authors":["P Henderson, T Hashimoto, M Lemley - arXiv preprint arXiv:2308.04635, 2023"],"snippet":"… The underlying datasets can range from crawls of the web (eg, CommonCrawl) to court opinions from CourtListener and even to books downloaded from BitTorrent trackers.This input data may be lightly filtered for hate speech and private information …","url":["https://arxiv.org/pdf/2308.04635"]}
{"year":"2023","title":"Who can verify this? Finding authorities for rumor verification in Twitter","authors":["F Haouari, T Elsayed, W Mansour - Information Processing & Management, 2023"],"snippet":"A large body of research work has proposed verification techniques for rumors spreading in social media that mainly relied on subjective evidence, eg, propagation networks or user interactions. Alternatively, in this work, we introduce the task of …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323001036"]}
{"year":"2023","title":"Who Killed the Winograd Schema Challenge?","authors":["H Neri, FG Cozman - Brazilian Conference on Intelligent Systems, 2023"],"snippet":"In which we investigate the technical issues surrounding the defeat, or perhaps the sudden assassination, of the Winograd Schema Challenge. We argue that, while the obvious suspect is the WinoGrande-based solution, the real cause of death was the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-45392-2_14"]}
{"year":"2023","title":"Why do Words with Negative Connotations Still Exist? A Corpus-Based Analysis of the Words 'Handicapped','Diffable', and 'Disability'","authors":["Y Yolanda, B Setyono - 2023"],"snippet":"This corpus-based study examines the persistence of negatively connoted words in the Indonesian, particularly focusing on cacat (handicapped). Cacat is compared to its synonyms, namely difabel (difable) and disabilitas (disability). The study employs …","url":["https://rupkatha.com/V15/n4/v15n415.pdf"]}
{"year":"2023","title":"Why You Should Give Your Students Automatic Process Feedback on Their Collaboration: Evidence from a Randomized Experiment","authors":["L Menzel, S Gombert, J Weidlich, A Fink, A Frey… - European Conference on …, 2023"],"snippet":"In Computer-Supported Collaborative Learning (CSCL), students learn in small groups to achieve learning benefits outside what would be possible for individual students. As in other forms of learning, students need feedback on the quality of their …","url":["https://link.springer.com/chapter/10.1007/978-3-031-42682-7_14"]}
{"year":"2023","title":"WiCE: Real-World Entailment for Claims in Wikipedia","authors":["R Kamoi, T Goyal, JD Rodriguez, G Durrett - arXiv preprint arXiv:2303.01432, 2023"],"snippet":"… For each claim c, we re-retrieve the cited web articles from Common Crawl.We automatically parse the cited articles’ (note that there might be more than one cited article) HTML to extract the article text. This process is often quite noisy and may …","url":["https://arxiv.org/pdf/2303.01432"]}
{"year":"2023","title":"Witscript 3: A Hybrid AI System for Improvising Jokes in a Conversation","authors":["J Toplyn - arXiv preprint arXiv:2301.02695, 2023"],"snippet":"Previous papers presented Witscript and Witscript 2, AI systems for improvising jokes in a conversation. Witscript generates jokes that rely on wordplay, whereas the jokes generated by Witscript 2 rely on common sense. This paper extends that …","url":["https://arxiv.org/pdf/2301.02695"]}
{"year":"2023","title":"WizardLM: Empowering Large Language Models to Follow Complex Instructions","authors":["C Xu, Q Sun, K Zheng, X Geng, P Zhao, J Feng, C Tao… - arXiv preprint arXiv …, 2023"],"snippet":"Training large language models (LLM) with open-domain instruction following data brings colossal success. However, manually creating such instruction data is very time-consuming and labor-intensive. Moreover, humans may struggle to produce …","url":["https://arxiv.org/pdf/2304.12244"]}
{"year":"2023","title":"Word Embedding for Bengali Language using Domain-related Corpus","authors":["A Bandyopadhyay, J Nair - 2023 International Conference on Inventive …, 2023"],"snippet":"… Of late, word embeddings from general corpus such as Wikipedia dump, and common crawl corpus are very famous to make word vectors. In the case of Indian languages also such type of corpus is used to make word vectors. But it suffers in …","url":["https://ieeexplore.ieee.org/abstract/document/10134311/"]}
{"year":"2023","title":"Word length and frequency effects on text reading are highly similar in 12 alphabetic languages","authors":["V Kuperman, S Schroeder, D Gnetov - 2023"],"snippet":"One of the most robust findings in research on eye-movement control in reading is that shorter and more frequent words are recognized faster and skipped more often than longer and less frequent words. These benchmark effects of word length and …","url":["https://files.osf.io/v1/resources/cbvjr/providers/osfstorage/63e3ee839b908d02d12aee42?action=download&direct&version=1"]}
{"year":"2023","title":"WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data","authors":["M Weber, C Siebenschuh, RM Butler, A Alexandrov… - Thirty-seventh Conference …, 2023"],"snippet":"… Similar to large-scale NLP dataset creation pipelines like CCNet [33], we use the Common Crawl web corpus 2 as our primary source of documents. We parse Common Crawl to collect urls pointing to MS Word documents embedded in …","url":["https://openreview.net/pdf?id=xewwYquInO"]}
{"year":"2023","title":"Working with Corpora in Translation Technology Teaching: Enhancing Aspects of Course Design","authors":["M Shuttleworth - Corpora and Translation Education: Advances and …, 2023"],"snippet":"This chapter offers a discussion of two linked areas that are relevant to the translation technology curriculum. Firstly, in the absence of a suitable cost-effective industry-standard terminology extraction utility—as well as the relative under-representation …","url":["https://link.springer.com/chapter/10.1007/978-981-99-6589-2_6"]}
{"year":"2023","title":"X-ABI: Toward Parameter-Efficient Multilingual Adapter-Based Inference for Cross-Lingual Transfer","authors":["AS Menon, K Anand - … Management, Analytics and Innovation: Proceedings of …, 2023"],"snippet":"… XLM-RoBERTa is a multilingual self-supervised transformers model that is pre-trained on 2.5 TB of filtered CommonCrawl data containing 100 … Table 6 is a comparison between XNLI accuracy and number of tokens present in the 2.5 TB of filtered …","url":["https://link.springer.com/chapter/10.1007/978-981-99-1414-2_23"]}
{"year":"2023","title":"xDial-Eval: A Multilingual Open-Domain Dialogue Evaluation Benchmark","authors":["C Zhang, LF D'Haro, C Tang, K Shi, G Tang, H Li"],"snippet":"Recent advancements in reference-free learned metrics for open-domain dialogue evaluation have been driven by the progress in pre-trained language models and the availability of dialogue data with high-quality human annotations. However …","url":["https://arxiv.org/pdf/2310.08958"]}
{"year":"2023","title":"XFEVER: Exploring Fact Verification across Languages","authors":["YC Chang, C Kruengkrai, J Yamagishi - arXiv preprint arXiv:2310.16278, 2023"],"snippet":"This paper introduces the Cross-lingual Fact Extraction and VERification (XFEVER) dataset designed for benchmarking the fact verification models across different languages. We constructed it by translating the claim and evidence texts of the Fact …","url":["https://arxiv.org/pdf/2310.16278"]}
{"year":"2023","title":"XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models","authors":["D Liang, H Gonen, Y Mao, R Hou, N Goyal… - arXiv preprint arXiv …, 2023"],"snippet":"Large multilingual language models typically rely on a single vocabulary shared across 100+ languages. As these models have increased in parameter count and depth, vocabulary size has remained largely unchanged. This vocabulary bottleneck …","url":["https://arxiv.org/pdf/2301.10472"]}
{"year":"2023","title":"XNLI 2.0: Improving XNLI dataset and performance on Cross Lingual Understanding (XLU)","authors":["AK Upadhyay, HK Upadhya - arXiv preprint arXiv:2301.06527, 2023"],"snippet":"Natural Language Processing systems are heavily dependent on the availability of annotated data to train practical models. Primarily, models are trained on English datasets. In recent times, significant advances have been made in multilingual …","url":["https://arxiv.org/pdf/2301.06527"]}
{"year":"2023","title":"xSIM++: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages","authors":["M Chen, K Heffernan, O Çelebi, A Mourachko… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce a new proxy score for evaluating bitext mining based on similarity in a multilingual embedding space: xSIM++. In comparison to xSIM, this improved proxy leverages rule-based approaches to extend English sentences in any evaluation set …","url":["https://arxiv.org/pdf/2306.12907"]}
{"year":"2023","title":"XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource Languages","authors":["D Taunk, S Sagare, A Patil, S Subramanian, M Gupta… - arXiv preprint arXiv …, 2023"],"snippet":"… 2020) was pretrained on CommonCrawl corpus using the BART objective where the input texts are noised by masking phrases and permuting sentences, and a single Transformer model is learned to recover the texts. Specifically, our mT5-base …","url":["https://arxiv.org/pdf/2303.12308"]}
{"year":"2023","title":"Yes but.. Can ChatGPT Identify Entities in Historical Documents?","authors":["CE González-Gallardo, E Boros, N Girdhar, A Hamdi… - arXiv preprint arXiv …, 2023","E Boros, N Girdhar, A Hamdi, JG Moreno, A Doucet"],"snippet":"Large language models (LLMs) have been leveraged for several years now, obtaining state-of-the-art performance in recognizing entities from modern documents. For the last few months, the conversational agent ChatGPT has \"prompted\" …","url":["https://arxiv.org/pdf/2303.17322","https://www.academia.edu/download/101050375/chatGPT.pdf"]}
{"year":"2023","title":"You Call This Archaeology? Evaluating Web Archives for Reproducible Web Security Measurements","authors":["F Hantke, S Calzavara, M Wilhelm, A Rabitti, B Stock - 2023","S Calzavara, F Hantke, M Wilhelm, A Rabitti, B Stock - 2023"],"snippet":"… Besides Memento-based archives, we also consider Common Crawl as a possible alternative source of archival data. Common Crawl … Besides Common Crawl, we consider a public list4 of web archives supporting the Memento protocol …","url":["https://swag.cispa.saarland/papers/calzavara2023archaeology.pdf","https://swag.cispa.saarland/papers/hantke2023archaeology.pdf"]}
{"year":"2023","title":"YUAN 2.0: A Large Language Model with Localized Filtering-based Attention","authors":["S Wu, X Zhao, S Wang, J Luo, L Li, X Chen, B Zhao… - arXiv preprint arXiv …, 2023"],"snippet":"In this work, the Localized Filtering-based Attention (LFA) is introduced to incorporate prior knowledge of local dependencies of natural language into Attention. Based on LFA, we develop and release Yuan 2.0, a large language model with …","url":["https://arxiv.org/pdf/2311.15786"]}
{"year":"2023","title":"Zero-shot cross-lingual transfer language selection using linguistic similarity","authors":["J Eronen, M Ptaszynski, F Masui - Information Processing & Management, 2023"],"snippet":"We study the selection of transfer languages for different Natural Language Processing tasks, specifically sentiment analysis, named entity recognition and dependency parsing. In order to select an optimal transfer language, we propose to …","url":["https://www.sciencedirect.com/science/article/pii/S030645732200351X"]}
{"year":"2023","title":"Zero-shot Cross-lingual Transfer With Learned Projections Using Unlabeled Target-Language Data","authors":["U Deb, R Parab, P Jyothi - The 61st Annual Meeting Of The Association For …, 2023"],"snippet":"Adapters have emerged as a parameter-efficient Transformer-based framework for cross-lingual transfer by inserting lightweight languagespecific modules (language adapters) and taskspecific modules (task adapters) within pretrained multilingual …","url":["https://www.cse.iitb.ac.in/~pjyothi/files/ACL2023a.pdf"]}
{"year":"2023","title":"Zero-shot Cross-lingual Transfer without Parallel Corpus","authors":["Y Zhang, X Han, B Wang - arXiv preprint arXiv:2310.04726, 2023"],"snippet":"Recently, although pre-trained language models have achieved great success on multilingual NLP (Natural Language Processing) tasks, the lack of training data on many tasks in low-resource languages still limits their performance. One effective …","url":["https://arxiv.org/pdf/2310.04726"]}
{"year":"2023","title":"Zero-Shot ECG Diagnosis with Large Language Models and Retrieval-Augmented Generation","authors":["H Yu, P Guo, A Sano - Machine Learning for Health (ML4H), 2023"],"snippet":"Recently, Large Language Models (LLMs) have become essential players in the deep learning domain. While their capabilities are evident across various textual tasks, this study aims to bridge the gap and explore the potential of leveraging LLMs …","url":["https://proceedings.mlr.press/v225/yu23b/yu23b.pdf"]}
{"year":"2023","title":"Zero-Shot Learning on Low-Resource Languages by Cross-Lingual Retrieval","authors":["E Nie"],"snippet":"Research on zero-shot learning on low-resource languages in NLP is motivated by inherent data scarcity of low-resource languages. On the contrary, languages with a large amount of both labeled and unlabeled resources are not fully utilized …","url":["https://www.cip.ifi.lmu.de/~nie/Files/Master_Thesis_Nie.pdf"]}
{"year":"2023","title":"Zero-Shot Slot and Intent Detection in Low-Resource Languages","authors":["SY Kwon, G Bhatia, EMB Nagoudi, AA Inciarte… - arXiv preprint arXiv …, 2023"],"snippet":"Intent detection and slot filling are critical tasks in spoken and natural language understanding for task-oriented dialog systems. In this work we describe our participation in the slot and intent detection for low-resource language varieties (SID4LR; …","url":["https://arxiv.org/pdf/2304.13292"]}
{"year":"2023","title":"Zero-Shot Speech Emotion Recognition Using Generative Learning with Reconstructed Prototypes","authors":["X Xu, J Deng, Z Zhang, Z Yang, BW Schuller - ICASSP 2023-2023 IEEE International …, 2023"],"snippet":"… For the prototype-reconstruction step, we employ the 300-dimensional fastText model considering 2 million word vectors (600 billion tokens) trained on Common Crawl [31]. Then, a three-fold emotion-independent Cross-Validation (CV) is …","url":["https://ieeexplore.ieee.org/abstract/document/10094888/"]}
{"year":"2023","title":"Zero-Shot Transfer Learning using Affix and Correlated Cross-Lingual Embeddings.","authors":["A Modupe, T Sindane, V Marivate - 2023"],"snippet":"Learning morphologically supplemented embedding spaces using cross-lingual models has become an active area of research and facilitated many research breakthroughs in various applications such as machine translation, named entity …","url":["https://www.authorea.com/doi/pdf/10.22541/au.167878643.36371140"]}
{"year":"2023","title":"Zhanglin Wu, Zhengzhe Yu, Zongyao Li, Daimeng Wei, Yuhao Xie, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Zhiqiang Rao, Shaojun Li, Song peng, Lizhi Lei, Hao …","authors":["X Chen - Machine Translation: 19th China Conference, CCMT …, 2023"],"snippet":"This paper presents Huawei Translation Service Center (HW-TSC)'s submission to the machine translation tasks of the 19th China Conference on Machine Translation (CCMT 2023). We participate in all machine translation tasks, including five bilingual …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=OYHgEAAAQBAJ&oi=fnd&pg=PA13&dq=commoncrawl&ots=UiY3rNSUOc&sig=KqCm2llH57sdbm9NHbTvEsbAR2A"]}
{"year":"2023","title":"Ziya2: Data-centric Learning is All LLMs Need","authors":["R Gan, Z Wu, R Sun, J Lu, X Wu, D Zhang, K Pan… - arXiv preprint arXiv …, 2023"],"snippet":"… First, we find that Common Crawl and other open-source datasets contain substantial duplication of web pages and thus use Bloomfilter5 to de-duplicate URLs, which significantly reduces the computational load required for subsequent content …","url":["https://arxiv.org/pdf/2311.03301"]}
{"year":"2023","title":"Zoology: Measuring and Improving Recall in Efficient Language Models","authors":["S Arora, S Eyuboglu, A Timalsina, I Johnson, M Poli… - arXiv preprint arXiv …, 2023"],"snippet":"Attention-free language models that combine gating and convolutions are growing in popularity due to their efficiency and increasingly competitive performance. To better understand these architectures, we pretrain a suite of 17 attention and \"gated-convolution\" …","url":["https://arxiv.org/pdf/2312.04927"]}
{"year":"2023","title":"Zootopi at HOPE2023IberLEF: Is Zero-Shot Chat-GPT the Future of Hope Speech Detection","authors":["A Ngo, HTH Tran - Proceedings of the Iberian Languages Evaluation …, 2023"],"snippet":"Hope Speech Detection is a Natural Language Processing (NLP) task where we aim to detect any message or text that can relax a hostile environment and inspire people in a time of suffering illness, stress, loneliness or depression with optimism …","url":["https://ceur-ws.org/Vol-3496/hope-paper6.pdf"]}