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Collections including paper arxiv:2506.01939

Yume: An Interactive World Generation Model

Paper • 2507.17744 • Published Jul 23 • 85
SSRL: Self-Search Reinforcement Learning

Paper • 2508.10874 • Published Aug 14 • 93
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

Paper • 2506.06941 • Published Jun 7 • 15
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 136
The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models

Paper • 2505.22617 • Published May 28 • 130

Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 260
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Paper • 2506.06395 • Published Jun 5 • 130
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Paper • 2506.05176 • Published Jun 5 • 72
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 272

Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 272
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 136
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

June 2025 - Top Papers

Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning

Paper • 2506.07044 • Published Jun 8 • 113
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning

Paper • 2506.09513 • Published Jun 11 • 98
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
Seedance 1.0: Exploring the Boundaries of Video Generation Models

Paper • 2506.09113 • Published Jun 10 • 101

Will It Still Be True Tomorrow? Multilingual Evergreen Question Classification to Improve Trustworthy QA

Paper • 2505.21115 • Published May 27 • 139
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 136

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

inference-optimization

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

Yume: An Interactive World Generation Model

Paper • 2507.17744 • Published Jul 23 • 85
SSRL: Self-Search Reinforcement Learning

Paper • 2508.10874 • Published Aug 14 • 93
The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

Paper • 2506.06941 • Published Jun 7 • 15
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

June 2025 - Top Papers

Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning

Paper • 2506.07044 • Published Jun 8 • 113
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning

Paper • 2506.09513 • Published Jun 11 • 98
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
Seedance 1.0: Exploring the Boundaries of Video Generation Models

Paper • 2506.09113 • Published Jun 10 • 101

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 136
The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models

Paper • 2505.22617 • Published May 28 • 130

Will It Still Be True Tomorrow? Multilingual Evergreen Question Classification to Improve Trustworthy QA

Paper • 2505.21115 • Published May 27 • 139
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 136

Reinforcement Pre-Training

Paper • 2506.08007 • Published Jun 9 • 260
Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models

Paper • 2506.06395 • Published Jun 5 • 130
Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Paper • 2506.05176 • Published Jun 5 • 72
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 272

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 272
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 136
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97

inference-optimization

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 181

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