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Collections including paper arxiv:2504.16084
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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 • 117 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 110 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 121
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about 4 hours ago
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Towards General-Purpose Model-Free Reinforcement Learning
Paper • 2501.16142 • Published • 30 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 121 -
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Paper • 2504.13837 • Published • 91 -
Learning to Reason under Off-Policy Guidance
Paper • 2504.14945 • Published • 66
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about 10 hours ago
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Step Back to Leap Forward: Self-Backtracking for Boosting Reasoning of Language Models
Paper • 2502.04404 • Published • 24 -
Learning Adaptive Parallel Reasoning with Language Models
Paper • 2504.15466 • Published • 33 -
TTRL: Test-Time Reinforcement Learning
Paper • 2504.16084 • Published • 55 -
THOUGHTTERMINATOR: Benchmarking, Calibrating, and Mitigating Overthinking in Reasoning Models
Paper • 2504.13367 • Published • 23