Collections
Discover the best community collections!
Collections including paper arxiv:2505.13417
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J1: Incentivizing Thinking in LLM-as-a-Judge via Reinforcement Learning
Paper • 2505.10320 • Published • 24 -
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
Paper • 2505.09343 • Published • 76 -
Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models
Paper • 2505.10554 • Published • 120 -
Scaling Reasoning can Improve Factuality in Large Language Models
Paper • 2505.11140 • Published • 7
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Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 120 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 146
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Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering
Paper • 2411.11504 • Published • 24 -
Top-nσ: Not All Logits Are You Need
Paper • 2411.07641 • Published • 24 -
Adaptive Decoding via Latent Preference Optimization
Paper • 2411.09661 • Published • 10 -
When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training
Paper • 2411.13476 • Published • 16
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AdaptThink: Reasoning Models Can Learn When to Think
Paper • 2505.13417 • Published • 83 -
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Paper • 2504.20571 • Published • 98 -
GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
Paper • 2601.05242 • Published • 230 -
Does Your Reasoning Model Implicitly Know When to Stop Thinking?
Paper • 2602.08354 • Published • 263
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CoRAG: Collaborative Retrieval-Augmented Generation
Paper • 2504.01883 • Published • 9 -
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
Paper • 2504.08837 • Published • 44 -
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model
Paper • 2504.10068 • Published • 30 -
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations
Paper • 2504.10481 • Published • 85
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Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 115 -
Reasoning Language Models: A Blueprint
Paper • 2501.11223 • Published • 33 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 32 -
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Paper • 2501.09686 • Published • 41
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Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 53 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29
-
AdaptThink: Reasoning Models Can Learn When to Think
Paper • 2505.13417 • Published • 83 -
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Paper • 2504.20571 • Published • 98 -
GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
Paper • 2601.05242 • Published • 230 -
Does Your Reasoning Model Implicitly Know When to Stop Thinking?
Paper • 2602.08354 • Published • 263
-
J1: Incentivizing Thinking in LLM-as-a-Judge via Reinforcement Learning
Paper • 2505.10320 • Published • 24 -
Insights into DeepSeek-V3: Scaling Challenges and Reflections on Hardware for AI Architectures
Paper • 2505.09343 • Published • 76 -
Beyond 'Aha!': Toward Systematic Meta-Abilities Alignment in Large Reasoning Models
Paper • 2505.10554 • Published • 120 -
Scaling Reasoning can Improve Factuality in Large Language Models
Paper • 2505.11140 • Published • 7
-
CoRAG: Collaborative Retrieval-Augmented Generation
Paper • 2504.01883 • Published • 9 -
VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning
Paper • 2504.08837 • Published • 44 -
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model
Paper • 2504.10068 • Published • 30 -
xVerify: Efficient Answer Verifier for Reasoning Model Evaluations
Paper • 2504.10481 • Published • 85
-
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 120 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 146
-
Evolving Deeper LLM Thinking
Paper • 2501.09891 • Published • 115 -
Reasoning Language Models: A Blueprint
Paper • 2501.11223 • Published • 33 -
Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident Even When They Are Wrong
Paper • 2501.09775 • Published • 32 -
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Paper • 2501.09686 • Published • 41
-
Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering
Paper • 2411.11504 • Published • 24 -
Top-nσ: Not All Logits Are You Need
Paper • 2411.07641 • Published • 24 -
Adaptive Decoding via Latent Preference Optimization
Paper • 2411.09661 • Published • 10 -
When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training
Paper • 2411.13476 • Published • 16
-
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 53 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 39 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 121 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 29