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Collections including paper arxiv:2404.06395

📑 Papers of Trending Models

Qwen2 Technical Report

Paper • 2407.10671 • Published Jul 15 • 153
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9 • 19
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output

Paper • 2407.03320 • Published Jul 3 • 92
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Paper • 2406.11931 • Published Jun 17 • 56

MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9 • 19

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 • 19
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2 • 34
Are large language models superhuman chemists?

Paper • 2404.01475 • Published Apr 1 • 15

Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11 • 83
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

Paper • 2404.10667 • Published Apr 16 • 14
Instruction-tuned Language Models are Better Knowledge Learners

Paper • 2402.12847 • Published Feb 20 • 24
DoRA: Weight-Decomposed Low-Rank Adaptation

Paper • 2402.09353 • Published Feb 14 • 24

Foundation Models

OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1 • 78
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Paper • 2403.05530 • Published Mar 8 • 59
StarCoder: may the source be with you!

Paper • 2305.06161 • Published May 9, 2023 • 29
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling

Paper • 2312.15166 • Published Dec 23, 2023 • 56

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

MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9 • 19

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Paper • 2403.03507 • Published Mar 6 • 182
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 65
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Paper • 2403.13372 • Published Mar 20 • 58
InternLM2 Technical Report

Paper • 2403.17297 • Published Mar 26 • 28

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 • 94
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

LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning

Paper • 2401.01325 • Published Jan 2 • 26
WaveCoder: Widespread And Versatile Enhanced Instruction Tuning with Refined Data Generation

Paper • 2312.14187 • Published Dec 20, 2023 • 49
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Paper • 2401.10891 • Published Jan 19 • 58
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9 • 19

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