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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

about 8 hours ago

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1 • 20
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1 • 74
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 135
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30 • 22

LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models

Paper • 2309.12307 • Published Sep 21, 2023 • 82
NEFTune: Noisy Embeddings Improve Instruction Finetuning

Paper • 2310.05914 • Published Oct 9, 2023 • 13
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling

Paper • 2312.15166 • Published Dec 23, 2023 • 55
Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon

Paper • 2401.03462 • Published Jan 7 • 25

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 33
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 29 days ago • 32
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 • 33
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9 • 18

Adapting Large Language Models via Reading Comprehension

Paper • 2309.09530 • Published Sep 18, 2023 • 69
TinyGSM: achieving >80% on GSM8k with small language models

Paper • 2312.09241 • Published Dec 14, 2023 • 33
How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 33
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 19 days ago • 118
Scaling Laws for Downstream Task Performance of Large Language Models

Paper • 2402.04177 • Published Feb 6 • 16
Orca 2: Teaching Small Language Models How to Reason

Paper • 2311.11045 • Published Nov 18, 2023 • 68
Orca-Math: Unlocking the potential of SLMs in Grade School Math

Paper • 2402.14830 • Published Feb 16 • 23

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 33
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Paper • 2401.16380 • Published Jan 29 • 45

Watermarking Makes Language Models Radioactive

Paper • 2402.14904 • Published Feb 22 • 21
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition

Paper • 2402.15220 • Published Feb 23 • 18
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 • 33

Sample Efficiency

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 33

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