Key papers

• AgentCPM-Report: Interleaving Drafting and Deepening for Open-Ended Deep Research (2026)
  Yishan Li et al.
  1.94
• The PokeAgent Challenge: Competitive and Long-Context Learning at Scale (2026)
  Seth Karten et al.
  1.94
• Eliciting Medical Reasoning with Knowledge-enhanced Data Synthesis: A Semi-Supervised Reinforcement Learning Approach (2026)
  Haolin Li et al.
  1.94
• RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains (2026)
  Haoxiang Jiang et al.
  1.94
• Risk Under Pressure: Compute-Aware Evaluation of Adversarial Robustness in Language Models (2026)
  Malikeh Ehghaghi et al.
  1.94
• EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL (2026)
  Minrui Xu et al.
  1.89
• DRIFT: Decoupled Rollouts and Importance-Weighted Fine-Tuning for Efficient Multi-Turn Optimization (2026)
  Jian Mu et al.
  1.89
• Accelerating RL Post-Training Rollouts via System-Integrated Speculative Decoding (2026)
  Hayate Iso et al.
  1.83
• Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation (2026)
  Zhuolin Yang et al.
  1.78
• PromptRL: Prompt Matters in RL for Flow-Based Image Generation (2026)
  Fu-Yun Wang et al.
  1.72
• Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations (2026)
  Wei Liu et al.
  1.72
• Learning to Detect Language Model Training Data via Active Reconstruction (2026)
  Junjie Oscar Yin et al.
  1.72
• An Empirical Study on Eliciting and Improving R1-like Reasoning Models (2025)
  Zhipeng Chen et al.
  1.28
• LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL (2025)
  Yingzhe Peng et al.
  1.28
• Optimizing Test-Time Compute via Meta Reinforcement Fine-Tuning (2025)
  Yuxiao Qu et al.
  1.28
• DAPO: An Open-Source LLM Reinforcement Learning System at Scale (2025)
  Qiying Yu et al.
  1.28
• Video-R1: Reinforcing Video Reasoning in MLLMs (2025)
  Kaituo Feng et al.
  1.28
• OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learning (2025)
  Zhaochen Su et al.
  1.28
• STAR-R1: Spatial TrAnsformation Reasoning by Reinforcing Multimodal LLMs (2025)
  Zongzhao Li et al.
  1.28
• Pixel Reasoner: Incentivizing Pixel-Space Reasoning with Curiosity-Driven Reinforcement Learning (2025)
  Alex Su et al.
  1.28
• AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning (2025)
  Yang Chen et al.
  1.28
• Synthetic Data RL: Task Definition Is All You Need (2025)
  Yiduo Guo et al.
  1.28
• MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs (2025)
  Jiakang Yuan et al.
  1.28
• Video-Holmes: Can MLLM Think Like Holmes for Complex Video Reasoning? (2025)
  Junhao Cheng et al.
  1.28
• ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models (2025)
  Mingjie Liu et al.
  1.28
• Play to Generalize: Learning to Reason Through Game Play (2025)
  Yunfei Xie et al.
  1.28
• On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification (2025)
  Yongliang Wu et al.
  1.28
• Klear-Reasoner: Advancing Reasoning Capability via Gradient-Preserving Clipping Policy Optimization (2025)
  Zhenpeng Su et al.
  1.28
• Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward (2025)
  Yong Deng et al.
  1.28
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency (2025)
  Weiyun Wang et al.
  1.28
• The Landscape of Agentic Reinforcement Learning for LLMs: A Survey (2025)
  Guibin Zhang et al.
  1.28
• Hunyuan-MT Technical Report (2025)
  Mao Zheng et al.
  1.28
• FrameThinker: Learning to Think with Long Videos via Multi-Turn Frame Spotlighting (2025)
  Zefeng He et al.
  1.28
• Thinking-Free Policy Initialization Makes Distilled Reasoning Models More Effective and Efficient Reasoners (2025)
  Xin Xu et al.
  1.28
• RewardMap: Tackling Sparse Rewards in Fine-grained Visual Reasoning via Multi-Stage Reinforcement Learning (2025)
  Sicheng Feng 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
• MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model (2025)
  Prasanna Mayilvahanan et al.
  1.28
• Agentic Design of Compositional Machines (2025)
  Wenqian Zhang et al.
  1.28
• Search Self-play: Pushing the Frontier of Agent Capability without Supervision (2025)
  Hongliang Lu et al.
  1.28
• Every Step Evolves: Scaling Reinforcement Learning for Trillion-Scale Thinking Model (2025)
  Ling Team et al.
  1.28
• SPARK: Stepwise Process-Aware Rewards for Reference-Free Reinforcement Learning (2025)
  Salman Rahman et al.
  1.28
• On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes (2023)
  Rishabh Agarwal et al.
  —
• PASTA: Pretrained Action-State Transformer Agents (2023)
  Raphael Boige et al.
  —
• RL for Consistency Models: Faster Reward Guided Text-to-Image Generation (2024)
  Owen Oertell et al.
  —
• Coffee-Gym: An Environment for Evaluating and Improving Natural Language Feedback on Erroneous Code (2024)
  Hyungjoo Chae et al.
  —
• WildLMa: Long Horizon Loco-Manipulation in the Wild (2024)
  Ri-Zhao Qiu et al.
  —