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Collections including paper arxiv:2402.09668

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1 • 21
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1 • 78
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 140
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30 • 25

PDFTriage: Question Answering over Long, Structured Documents

Paper • 2309.08872 • Published Sep 16, 2023 • 53
Adapting Large Language Models via Reading Comprehension

Paper • 2309.09530 • Published Sep 18, 2023 • 75
Table-GPT: Table-tuned GPT for Diverse Table Tasks

Paper • 2310.09263 • Published Oct 13, 2023 • 39
Context-Aware Meta-Learning

Paper • 2310.10971 • Published Oct 17, 2023 • 16

Efficient LMs - Small Models

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 38
SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Paper • 2401.15024 • Published Jan 26 • 67
SHERL: Synthesizing High Accuracy and Efficient Memory for Resource-Limited Transfer Learning

Paper • 2407.07523 • Published Jul 10 • 4
Spectra: A Comprehensive Study of Ternary, Quantized, and FP16 Language Models

Paper • 2407.12327 • Published Jul 17 • 75

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 38
A Survey on Data Selection for LLM Instruction Tuning

Paper • 2402.05123 • Published Feb 4 • 3

Pre-training Small Base LMs with Fewer Tokens

Paper • 2404.08634 • Published Apr 12 • 33
Ziya2: Data-centric Learning is All LLMs Need

Paper • 2311.03301 • Published Nov 6, 2023 • 16
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 38
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9 • 19

Adapting Large Language Models via Reading Comprehension

Paper • 2309.09530 • Published Sep 18, 2023 • 75
TinyGSM: achieving >80% on GSM8k with small language models

Paper • 2312.09241 • Published Dec 14, 2023 • 36
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 38
Let GPT be a Math Tutor: Teaching Math Word Problem Solvers with Customized Exercise Generation

Paper • 2305.14386 • Published May 22, 2023

Empowering SLMs

Collection of resources focusing on making Small Language Models (SLMs) better at various tasks

OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework

Paper • 2404.14619 • Published Apr 22 • 124
Scaling Laws for Downstream Task Performance of Large Language Models

Paper • 2402.04177 • Published Feb 6 • 17
Orca 2: Teaching Small Language Models How to Reason

Paper • 2311.11045 • Published Nov 18, 2023 • 70
Orca-Math: Unlocking the potential of SLMs in Grade School Math

Paper • 2402.14830 • Published Feb 16 • 24

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 38
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Paper • 2401.16380 • Published Jan 29 • 46

Watermarking Makes Language Models Radioactive

Paper • 2402.14904 • Published Feb 22 • 22
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition

Paper • 2402.15220 • Published Feb 23 • 19
GPTVQ: The Blessing of Dimensionality for LLM Quantization

Paper • 2402.15319 • Published Feb 23 • 19
DiLightNet: Fine-grained Lighting Control for Diffusion-based Image Generation

Paper • 2402.11929 • Published Feb 19 • 9

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 38

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