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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 78 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 140 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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Collections including paper arxiv:2408.02545
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WikiChat: Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia
Paper • 2305.14292 • Published • 1 -
Harnessing Retrieval-Augmented Generation (RAG) for Uncovering Knowledge Gaps
Paper • 2312.07796 • Published -
RAGAS: Automated Evaluation of Retrieval Augmented Generation
Paper • 2309.15217 • Published • 3 -
Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering
Paper • 2210.02627 • Published
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MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
Paper • 2309.04662 • Published • 22 -
Neurons in Large Language Models: Dead, N-gram, Positional
Paper • 2309.04827 • Published • 16 -
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
Paper • 2309.05516 • Published • 9 -
DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs
Paper • 2309.03907 • Published • 8