Papers

• On-Policy Self-Distillation for Reasoning Compression (2026)
  Hejian Sang et al.
  1.94
• OPRD: On-Policy Representation Distillation (2026)
  Shenzhi Yang et al.
  1.94
• TIP: Token Importance in On-Policy Distillation (2026)
  Yuanda Xu et al.
  1.83
• An Empirical Study on Eliciting and Improving R1-like Reasoning Models (2025)
  Zhipeng Chen et al.
  1.28
• DAPO: An Open-Source LLM Reinforcement Learning System at Scale (2025)
  Qiying Yu et al.
  1.28
• Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models (2025)
  Ruikang Liu et al.
  1.28
• Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought (2025)
  Yi Peng et al.
  1.28
• AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning (2025)
  Yang Chen et al.
  1.28
• Kinetics: Rethinking Test-Time Scaling Laws (2025)
  Ranajoy Sadhukhan et al.
  1.28
• Reasoning or Memorization? Unreliable Results of Reinforcement Learning Due to Data Contamination (2025)
  Mingqi Wu et al.
  1.28
• Klear-Reasoner: Advancing Reasoning Capability via Gradient-Preserving Clipping Policy Optimization (2025)
  Zhenpeng Su et al.
  1.28
• Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning (2025)
  Vaishnavi Shrivastava et al.
  1.28
• CWM: An Open-Weights LLM for Research on Code Generation with World Models (2025)
  FAIR CodeGen team et al.
  1.28
• MixReasoning: Switching Modes to Think (2025)
  Haiquan Lu et al.
  1.28
• AlphaApollo: Orchestrating Foundation Models and Professional Tools into a Self-Evolving System for Deep Agentic Reasoning (2025)
  Zhanke Zhou et al.
  1.28
• MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model (2025)
  Prasanna Mayilvahanan et al.
  1.28