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Collections including paper arxiv:2404.09937

LM Capabilities and Scaling

Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15 • 27
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9 • 21
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2 • 35
Are large language models superhuman chemists?

Paper • 2404.01475 • Published Apr 1 • 16

Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15 • 27

Interesting Papers

Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11 • 84
LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Paper • 2404.05961 • Published Apr 9 • 64
Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15 • 27
Multi-Head Mixture-of-Experts

Paper • 2404.15045 • Published Apr 23 • 59

Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15 • 27
TransformerFAM: Feedback attention is working memory

Paper • 2404.09173 • Published Apr 14 • 43

Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset

Paper • 2403.09029 • Published Mar 14 • 54
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

Paper • 2403.12968 • Published Mar 19 • 24
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 67
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking

Paper • 2403.09629 • Published Mar 14 • 72

Foundation AI Papers

Curated List of Must-Reads on LLM reasoning at Temus AI team

Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models

Paper • 2310.04406 • Published Oct 6, 2023 • 8
Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15 • 99
ICDPO: Effectively Borrowing Alignment Capability of Others via In-context Direct Preference Optimization

Paper • 2402.09320 • Published Feb 14 • 6
Self-Discover: Large Language Models Self-Compose Reasoning Structures

Paper • 2402.03620 • Published Feb 6 • 109

Self-Discover: Large Language Models Self-Compose Reasoning Structures

Paper • 2402.03620 • Published Feb 6 • 109
Customizing Language Model Responses with Contrastive In-Context Learning

Paper • 2401.17390 • Published Jan 30
InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning

Paper • 2402.06332 • Published Feb 9 • 18
Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15 • 99

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1 • 21
Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30 • 16
ReFT: Reasoning with Reinforced Fine-Tuning

Paper • 2401.08967 • Published Jan 17 • 28
The Impact of Reasoning Step Length on Large Language Models

Paper • 2401.04925 • Published Jan 10 • 16

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Paper • 2401.10774 • Published Jan 19 • 54
APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Paper • 2401.06761 • Published Jan 12 • 1
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache

Paper • 2401.02669 • Published Jan 5 • 14
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 51

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