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Collections including paper arxiv:2501.18009

Reasoning, Thinking, RL and Test-Time Scaling

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search

Paper • 2412.18319 • Published Dec 24, 2024 • 39
Token-Budget-Aware LLM Reasoning

Paper • 2412.18547 • Published Dec 24, 2024 • 46
Efficiently Serving LLM Reasoning Programs with Certaindex

Paper • 2412.20993 • Published Dec 30, 2024 • 37
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners

Paper • 2412.17256 • Published Dec 23, 2024 • 47

Large Language Models Think Too Fast To Explore Effectively

Paper • 2501.18009 • Published Jan 29 • 24
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
Intuitive physics understanding emerges from self-supervised pretraining on natural videos

Paper • 2502.11831 • Published Feb 17 • 20
Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity

Paper • 2502.13063 • Published Feb 18 • 72

Large Language Models Think Too Fast To Explore Effectively

Paper • 2501.18009 • Published Jan 29 • 24
Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs

Paper • 2501.18585 • Published Jan 30 • 62

2025 LLM Papers on Hugging Face with Japanese Memos

MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models

Paper • 2501.02955 • Published Jan 6 • 44
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining

Paper • 2501.00958 • Published Jan 1 • 107
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding

Paper • 2501.12380 • Published Jan 21 • 85
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos

Paper • 2501.09781 • Published Jan 16 • 28

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 • 81
Table-GPT: Table-tuned GPT for Diverse Table Tasks

Paper • 2310.09263 • Published Oct 13, 2023 • 41
Context-Aware Meta-Learning

Paper • 2310.10971 • Published Oct 17, 2023 • 17

Evolving Deeper LLM Thinking

Paper • 2501.09891 • Published Jan 17 • 115
PaSa: An LLM Agent for Comprehensive Academic Paper Search

Paper • 2501.10120 • Published Jan 17 • 53
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong

Paper • 2501.09775 • Published Jan 16 • 33
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario

Paper • 2501.10132 • Published Jan 17 • 22

Large Language Models Think Too Fast To Explore Effectively

Paper • 2501.18009 • Published Jan 29 • 24
s1: Simple test-time scaling

Paper • 2501.19393 • Published Jan 31 • 124
Scalable-Softmax Is Superior for Attention

Paper • 2501.19399 • Published Jan 31 • 22
SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers

Paper • 2502.20545 • Published Feb 27 • 22

Large Language Models Think Too Fast To Explore Effectively

Paper • 2501.18009 • Published Jan 29 • 24
Gated recurrent neural networks discover attention

Paper • 2309.01775 • Published Sep 4, 2023 • 10
Self-Rewarding Vision-Language Model via Reasoning Decomposition

Paper • 2508.19652 • Published Aug 27 • 84

On Memorization of Large Language Models in Logical Reasoning

Paper • 2410.23123 • Published Oct 30, 2024 • 18
LLMs Do Not Think Step-by-step In Implicit Reasoning

Paper • 2411.15862 • Published Nov 24, 2024 • 11
Training Large Language Models to Reason in a Continuous Latent Space

Paper • 2412.06769 • Published Dec 9, 2024 • 90
Deliberation in Latent Space via Differentiable Cache Augmentation

Paper • 2412.17747 • Published Dec 23, 2024 • 32

LM Capabilities and Scaling

Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15, 2024 • 28
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9, 2024 • 24
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2, 2024 • 37
Are large language models superhuman chemists?

Paper • 2404.01475 • Published Apr 1, 2024 • 19

Reasoning, Thinking, RL and Test-Time Scaling

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search

Paper • 2412.18319 • Published Dec 24, 2024 • 39
Token-Budget-Aware LLM Reasoning

Paper • 2412.18547 • Published Dec 24, 2024 • 46
Efficiently Serving LLM Reasoning Programs with Certaindex

Paper • 2412.20993 • Published Dec 30, 2024 • 37
B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners

Paper • 2412.17256 • Published Dec 23, 2024 • 47

Evolving Deeper LLM Thinking

Paper • 2501.09891 • Published Jan 17 • 115
PaSa: An LLM Agent for Comprehensive Academic Paper Search

Paper • 2501.10120 • Published Jan 17 • 53
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong

Paper • 2501.09775 • Published Jan 16 • 33
ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario

Paper • 2501.10132 • Published Jan 17 • 22

Large Language Models Think Too Fast To Explore Effectively

Paper • 2501.18009 • Published Jan 29 • 24
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
Intuitive physics understanding emerges from self-supervised pretraining on natural videos

Paper • 2502.11831 • Published Feb 17 • 20
Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity

Paper • 2502.13063 • Published Feb 18 • 72

Large Language Models Think Too Fast To Explore Effectively

Paper • 2501.18009 • Published Jan 29 • 24
s1: Simple test-time scaling

Paper • 2501.19393 • Published Jan 31 • 124
Scalable-Softmax Is Superior for Attention

Paper • 2501.19399 • Published Jan 31 • 22
SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers

Paper • 2502.20545 • Published Feb 27 • 22

Large Language Models Think Too Fast To Explore Effectively

Paper • 2501.18009 • Published Jan 29 • 24
Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs

Paper • 2501.18585 • Published Jan 30 • 62

Large Language Models Think Too Fast To Explore Effectively

Paper • 2501.18009 • Published Jan 29 • 24
Gated recurrent neural networks discover attention

Paper • 2309.01775 • Published Sep 4, 2023 • 10
Self-Rewarding Vision-Language Model via Reasoning Decomposition

Paper • 2508.19652 • Published Aug 27 • 84

2025 LLM Papers on Hugging Face with Japanese Memos

MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models

Paper • 2501.02955 • Published Jan 6 • 44
2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining

Paper • 2501.00958 • Published Jan 1 • 107
MMVU: Measuring Expert-Level Multi-Discipline Video Understanding

Paper • 2501.12380 • Published Jan 21 • 85
VideoWorld: Exploring Knowledge Learning from Unlabeled Videos

Paper • 2501.09781 • Published Jan 16 • 28

On Memorization of Large Language Models in Logical Reasoning

Paper • 2410.23123 • Published Oct 30, 2024 • 18
LLMs Do Not Think Step-by-step In Implicit Reasoning

Paper • 2411.15862 • Published Nov 24, 2024 • 11
Training Large Language Models to Reason in a Continuous Latent Space

Paper • 2412.06769 • Published Dec 9, 2024 • 90
Deliberation in Latent Space via Differentiable Cache Augmentation

Paper • 2412.17747 • Published Dec 23, 2024 • 32

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 • 81
Table-GPT: Table-tuned GPT for Diverse Table Tasks

Paper • 2310.09263 • Published Oct 13, 2023 • 41
Context-Aware Meta-Learning

Paper • 2310.10971 • Published Oct 17, 2023 • 17

LM Capabilities and Scaling

Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15, 2024 • 28
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Paper • 2404.06395 • Published Apr 9, 2024 • 24
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2, 2024 • 37
Are large language models superhuman chemists?

Paper • 2404.01475 • Published Apr 1, 2024 • 19

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