Key papers

• Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning (2026)
  Zhenyu Hou et al.
  10.35
• Convergence Of Policy Gradient Methods For Finite-horizon Exploratory Linear-quadratic Control Problems (2022)
  Michael Giegrich, Christoph Reisinger, Yufei Zhang
  9.23
• Compatible Natural Gradient Policy Search (2019)
  Joni Pajarinen, Hong Linh Thai, Riad Akrour, et al.
  9.23
• TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning (2025)
  Zhepei Wei et al.
  7.52
• SimKO: Simple Pass@K Policy Optimization (2025)
  Ruotian Peng et al.
  6.80
• Holistic Data Scheduler for LLM Pre-training via Multi-Objective Reinforcement Learning (2026)
  Chenhao Dang et al.
  6.43
• RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies (2026)
  Tianxing Chen et al.
  5.88
• Playing 20 Question Game with Policy-Based Reinforcement Learning (2018)
  Huang Hu et al.
  5.24
• Conformal Policy Learning For Sensorimotor Control Under Distribution Shifts (2023)
  Huang Huang, Satvik Sharma, Antonio Loquercio, et al.
  5.24
• Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization (2026)
  Xuefeng Liu et al.
  5.01
• Cross-Platform Control for Autonomous Surface Vehicles via Adaptive Reinforcement Learning (2026)
  Ruiheng Jiang et al.
  5.01
• Gradient-Based Speech-to-Text Alignment for Any ASR Model: From CTC to Speech LLMs (2026)
  Albert Zeyer et al.
  5.01
• Geometric--Nongeometric Optimizer Calculus: A Modular Language for Reachable Gradient Methods (2026)
  Zavier Li
  5.01
• Diverse Exploration Via Conjugate Policies For Policy Gradient Methods (2019)
  Andrew Cohen, Xingye Qiao, Lei Yu, et al.
  4.52
• Verifiable Rewards for Calibrated Probabilistic Forecasting (2026)
  Sadanand Singh et al.
  4.39
• Learning Gait-Aware Quadruped Locomotion with Temporal Logic Specifications (2026)
  Merve Atasever et al.
  4.39
• Flow-Map GRPO: Reinforcement Learning for Few-Step Flow-Map Generators via Anchored Stochastic Composition (2026)
  Zhiqi Li et al.
  4.39
• Don't Let Gains FADE: Breaking Down Policy Gradient Weights in RL (2026)
  Juliette Decugis et al.
  4.39
• Wind-Aware Reinforcement Learning Control of a Small Quadrotor Using Learned Onboard Wind Estimation in Simulated Atmospheric Turbulence (2026)
  Abdullah Al Tasim et al.
  4.39
• Learning the Supports for Categorical Critic in Reinforcement Learning (2026)
  Jen-Yen Chang et al.
  4.39
• Weak-to-Strong Generalization via Direct On-Policy Distillation (2026)
  Shiyuan Feng et al.
  4.39
• Ad Headline Generation using Self-Critical Masked Language Model (2026)
  Yashal Shakti Kanungo et al.
  4.39
• Behavior Leverage Imbalance in Multi-Teacher On-Policy Distillation (2026)
  Jiabin Shen et al.
  4.39
• GIFT: Geometry-Informed Low-precision Gradient Communication for LLM Pretraining (2026)
  Jieying Wang et al.
  4.39
• Gradient-free Riemannian Langevin Sampler (2026)
  Ricardo Baptista et al.
  4.39
• Selective Timestep Weighting and Advantage-Based Replay for Sample-Efficient Diffusion RLHF (2026)
  Eric Zhu et al.
  4.39
• Safety-Contract Graph Multi-Agent Reinforcement Learning for Autonomous Network Security Response (2026)
  Jose Luis Lima de Jesus Silva
  4.33
• CSPO: Constraint-Sensitive Policy Optimization for Safe Reinforcement Learning (2026)
  Ayoub Belouadah et al.
  4.33
• Learning Coordinated Preference for Multi-Objective Multi-Agent Reinforcement Learning (2026)
  Pengxin Wang et al.
  4.33
• Beyond Reward Engineering: A Data Recipe for Long-Context Reinforcement Learning (2026)
  Xiaoyue Xu et al.
  4.33
• Weight-Space Geometry of Offline Reasoning Training (2026)
  Aleksandr Nikolich et al.
  4.33
• KLip-PPO: A per-sample KL perspective on PPO-Clip (2026)
  Riccardo Colletti et al.
  4.33
• Learning to Trigger: Reinforcement Learning at the Large Hadron Collider (2026)
  Zixin Ding et al.
  4.33
• Reinforcement Learning for Computer-Use Agents with Autonomous Evaluation (2026)
  Marta Sumyk et al.
  4.33
• LaGO: Latent Action Guidance for Online Reinforcement Learning (2026)
  Kuan-Yen Liu et al.
  4.33
• ExTra: Exploratory Trajectory Optimization for Language Model Reinforcement Learning (2026)
  Wenyang Hu et al.
  4.33
• Bias-Controlled Primal-Dual Natural Actor-Critic: Optimal Rates for Constrained Multi-Objective Average-Reward RL (2026)
  Ankur Naskar et al.
  4.33
• Learning with a Single Rollout via Monte Carlo Pass@k Critic (2026)
  Fengdi Che et al.
  4.33
• Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning (2026)
  Bang Giang Le et al.
  4.33
• Power-Budgeted Underwater Vehicle Control via Constrained Reinforcement Learning (2026)
  Yinuo Wang et al.
  4.33
• Memory-Efficient Policy Libraries with Low-Rank Adaptation in Reinforcement Learning (2026)
  Samuel Valland Lyngset et al.
  4.33
• Semantic Consistency Policy Optimization for Reinforcement Learning of LLM Agents (2026)
  Peng Xu et al.
  4.33
• FORCE: Efficient VLA Reinforcement Fine-Tuning via Value-Calibrated Warm-up and Self-Distillation (2026)
  Shuyi Zhang et al.
  4.33
• Regularized Reward-Punishment Reinforcement Learning (2026)
  Jiexin Wang et al.
  4.33
• TAPE: Leveraging Agent Topology For Cooperative Multi-agent Policy Gradient (2023)
  Xingzhou Lou, Junge Zhang, Timothy J. Norman, et al.
  3.58
• Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation (2026)
  Shenghui Zhang et al.
  3.51
• E-MRL: Cross-view Aligned Evidence-driven Multimodal Reinforcement Learning for Reliable 3D Tumor Analysis (2026)
  Sijing Li et al.
  3.45
• Solving Markov Decision Processes with Future Information via MPC (2026)
  Shambhuraj Sawant et al.
  3.45
• Retroactive Advantage Correction: Closed-Form V-Trace Bias Correction for Delay-Aware RLHF (2026)
  Arnav Raj
  3.45
• Statistical Decision Theory with Counterfactual Loss (2025)
  Benedikt Koch et al.
  2.91
• Reward-SQL: Boosting Text-to-SQL via Stepwise Reasoning and Process-Supervised Rewards (2025)
  Yuxin Zhang et al.
  2.82
• RIDGECUT: Learning Graph Partitioning with Rings and Wedges (2025)
  Qize Jiang et al.
  2.29
• Analysis Of Off-policy Multi-step Td-learning With Linear Function Approximation (2024)
  Donghwan Lee
  2.26
• Recursive Least Squares Policy Control With Echo State Network (2022)
  Chunyuan Zhang, Chao Liu, Qi Song, et al.
  2.26
• Augmenting Policy Learning With Routines Discovered From A Single Demonstration (2020)
  Zelin Zhao, Chuang Gan, Jiajun Wu, et al.
  2.26
• How Log-barrier Helps Exploration In Policy Optimization (2026)
  Leonardo Cesani, Matteo Papini, Marcello Restelli
  1.94
• A Policy-driven DRL Framework For System-level Tradeoff Control In Nr-u/wi-fi Coexistence (2026)
  Po-Heng Chou, Yi-Fang Yu, Shou-Yu Chen, et al.
  1.94
• CAPO: Counterfactual Credit Assignment In Sequential Cooperative Teams (2026)
  Shripad Deshmukh, Jayakumar Subramanian, Raghavendra Addanki, et al.
  1.94
• Robust Adversarial Policy Optimization Under Dynamics Uncertainty (2026)
  Mintae Kim, Koushil Sreenath
  1.94
• Stabilizing The Q-gradient Field For Policy Smoothness In Actor-critic (2026)
  Jeong Woon Lee, Kyoleen Kwak, Daeho Kim, et al.
  1.94