Sample-Efficient RL

RL: Reinforcement Learning

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Overview

Sample-efficient reinforcement learning aims to reduce the experience needed to learn useful policies, especially when interaction is slow, costly, or risky. Common approaches improve exploration with optimism or uncertainty estimates, reuse data through replay and demonstrations, learn models for planning, or exploit structure such as hierarchy, symmetry, and known dynamics. These methods are studied in settings from tabular and robust decision processes to MuJoCo and Atari control, robotics, and language-model training with verifiable rewards. The field balances empirical gains and PAC or regret guarantees against challenges such as stale replay, model error, limited data coverage, and differences between sample counts and wall-clock cost.

Latest papers

CardsList

253 papers30 papers in the last four weeks, up 150% on the four weeks before. 0.2% of all new papers.

  1. Efficient RLVR Training via Weighted Mutual Information Data Selection

    Mar 2, 2026Xinyu Zhou, Boyu Zhu, Haotian Zhang +2Reinforcement LearningRL for Language Model Reasoning

    HKUST(GZ) · UCL · Kuaishou Technology +1

  2. SEAR: Sample Efficient Action Chunking Reinforcement Learning

    Mar 2, 2026C. F. Maximilian Nagy, Onur Celik, Emiliyan Gospodinov +4Reinforcement LearningSample-Efficient RL

    Autonomous Learning Robots, Karlsruhe Institute of Technology · FZI Forschungszentrum Informatik, Karlsruhe

  3. Rethinking Policy Diversity in Ensemble Policy Gradient in Large-Scale Reinforcement Learning

    Mar 2, 2026Naoki Shitanda, Motoki Omura, Tatsuya Harada +1Policy Gradient MethodsRL Exploration

    The University of Tokyo, Tokyo, Japan · RIKEN Center for Advanced Intelligence Project, Tokyo, Japan

  4. PAC Guarantees for Reinforcement Learning: Sample Complexity, Coverage, and Structure

    Mar 1, 2026Joshua SteierFunction Approximation in RLReinforcement Learning

  5. Actor-Critic Pretraining for Proximal Policy Optimization

    Feb 27, 2026Andreas Kernbach, Amr Elsheikh, Nicolas Grupp +2Robotic RLSample-Efficient RL

    Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Stuttgart, Germany · Institute of Industrial Manufacturing and Management IFF, University of Stuttgart, Germany · Institute for Control Engineering of Machine Tools and Manufacturing Units ISW, University of Stuttgart, Germany +1

  6. Regret-Guided Search Control for Efficient Learning in AlphaZero

    Feb 24, 2026Yun-Jui Tsai, Wei-Yu Chen, Yan-Ru Ju +2Reinforcement LearningGame-Playing Agents

    Department of Computer Science, National Yang Ming Chiao Tung University, Taiwan · Institute of Information Science, Academia Sinica, Taiwan · College of Computing, Georgia Institute of Technology

  7. CACTO-BIC: Scalable Actor-Critic Learning via Biased Sampling and GPU-Accelerated Trajectory Optimization

    Feb 23, 2026Elisa Alboni, Pietro Noah Crestaz, Elias Fontanari +1Actor-Critic MethodsTrajectory Optimization

    Dept. of Industrial Engineering, University of Trento, Italy · LAAS-CNRS, Université de Toulouse, CNRS, Toulouse, France

  8. VariBASed: Variational Bayes-Adaptive Sequential Monte-Carlo Planning for Deep Reinforcement Learning

    Feb 21, 2026Joery A. de Vries, Jinke He, Yaniv Oren +3Bayesian RLSample-Efficient RL

    Trent AI Ltd, London, United Kingdom · EEMCS, Delft University of Technology, Delft, the Netherlands

  9. Flow Matching with Injected Noise for Offline-to-Online Reinforcement Learning

    Feb 20, 2026Yongjae Shin, Jongseong Chae, Jongeui Park +1Offline-To-Online RLSample-Efficient RL

    KAIST

  10. Deep Reinforcement Learning for Optimizing Energy Consumption in Smart Grid Systems

    Feb 20, 2026Abeer Alsheikhi, Amirfarhad Farhadi, Azadeh ZamanifarSample-Efficient RLPower Systems

    School of Computer Engineering, Iran university of Science and Technology, Tehran, Iran · Department of Computer Engineering, SR.C, Islamic Azad university, Tehran, Iran

  11. Learning Optimal and Sample-Efficient Decision Policies with Guarantees

    Feb 20, 2026Daqian ShaoReinforcement LearningSample-Efficient RL

    Wolfson College University of Oxford

  12. Memory-Based Advantage Shaping for LLM-Guided Reinforcement Learning

    Feb 20, 2026Narjes Nourzad, Carlee Joe-WongMemory-Augmented RLReinforcement Learning

    University of Southern California · Carnegie Mellon University

  13. MIRA: Memory-Integrated Reinforcement Learning Agent with Limited LLM Guidance

    Feb 20, 2026Narjes Nourzad, Carlee Joe-WongMemory-Augmented RLReinforcement Learning

    University of Southern California, Electrical and Computer Engineering, Los Angeles, CA 90007, USA · Carnegie Mellon University, Electrical and Computer Engineering, Pittsburgh, PA 15213, USA

  14. MASPO: Unifying Gradient Utilization, Probability Mass, and Signal Reliability for Robust and Sample-Efficient LLM Reasoning

    Feb 19, 2026Xiaoliang Fu, Jiaye Lin, Yangyi Fang +7RL for Language ModelsRL for Language Model Reasoning

    Meituan · Fudan University · Tsinghua University +2

  15. Retrospective In-Context Learning for Temporal Credit Assignment with Large Language Models

    Feb 19, 2026Wen-Tse Chen, Jiayu Chen, Fahim Tajwar +4Step-Level Credit Assignment in RLSparse-Reward RL

    Carnegie Mellon University · The University of Hong Kong · Stanford University

  16. Improved Bounds for Reward-Agnostic and Reward-Free Exploration

    Feb 18, 2026Oran Ridel, Alon CohenRL ExplorationReward-Free RL

    Department of Engineering, Tel Aviv University, Tel Aviv, Israel. · Google Research, Tel Aviv, Israel.

  17. Regret and Sample Complexity of Online Q-Learning via Concentration of Stochastic Approximation with Time-Inhomogeneous Markov Chains

    Feb 18, 2026Rahul Singh, Siddharth Chandak, Eric Moulines +2Regret Minimization in RLQ-Learning

    MBZUAI, UAE · Stanford University, USA · EPITA, France +1

  18. CDRL: A Reinforcement Learning Framework Inspired by Cerebellar Circuits and Dendritic Computational Strategies

    Feb 17, 2026Sibo Zhang, Rui Jing, Liangfu Lv +2Reinforcement LearningSample-Efficient RL

    Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.

  19. Near-Optimal Sample Complexity for Online Constrained MDPs

    Feb 16, 2026Chang Liu, Yunfan Li, Lin F. YangConstrained RLSafe RL

    University of California, Los Angeles

  20. VLM-Guided Experience Replay

    Feb 2, 2026Elad Sharony, Tom Jurgenson, Orr Krupnik +2Reinforcement LearningPrioritized Experience Replay

    Technion · ForSight Robotics · Nvidia Research

  21. Agile Reinforcement Learning through Separable Neural Architecture and Applications

    Jan 30, 2026Rajib Mostakim, Reza T. Batley, Sourav SahaRL ControlNeural Network Approximation Theory

    Department of Mechanical Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh · Kevin T. Crofton Department of Aerospace and Ocean Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

  22. HeaPA: Difficulty-Aware Heap Sampling and On-Policy Query Augmentation for LLM Reinforcement Learning

    Jan 30, 2026Weiqi Wang, Xin Liu, Binxuan Huang +13RL for Language ModelsRL for Language Model Reasoning

    Stores Foundational AI, Amazon Inc., Palo Alto, CA, USA · Department of Computer Science and Engineering, HKUST, Hong Kong SAR, China

  23. Can David Beat Goliath? On Multi-Hop Reasoning with Resource-Constrained Agents

    Jan 29, 2026Hojae Han, Heeyun Jung, Jongyoon Kim +1RL for Language Model ReasoningMulti-Hop QA

    ETRI · The University of Hong Kong · Seoul National University

  24. CLEANER: Self-Purified Trajectories Boost Agentic Reinforcement Learning

    Jan 21, 2026Tianshi Xu, Yuteng Chen, Meng LiAgentic RLReinforcement Learning

    Peking University · NTU, Singapore

  25. Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions

    Jan 21, 2026Asim H. Gazi, Yongyi Guo, Daiqi Gao +3Non-Stationary RLReinforcement Learning

    Department of Computer Science, Harvard University · Department of Statistics, Harvard University · Department of Statistics, University of Wisconsin–Madison +2

  26. GDEPO: Group Dual-dynamic and Equal-right Advantage Policy Optimization for Sample-Efficient Reinforcement Learning

    Jan 11, 2026Zhengqing Yan, Fan Guo, Xinyang Liu +5Group Relative Policy OptimizationReinforcement Learning with Verifiable Rewards

    State Key Laboratory of Engines, Tianjin University, 300354 Tianjin, China. · Artificial Intelligence Center, Cylingo Group, 100080 Beijing, China.

  27. Symmetry-Aware Steering of Equivariant Diffusion Policies: Benefits and Limits

    Dec 12, 2025Minwoo Park, Junwoo Chang, Jongeun Choi +1Diffusion PolicyRL for Diffusion Models

    Yonsei University, Seoul 03722, Republic of Korea · University of California, Berkeley, CA 94720, USA

  28. Auto-exploration for online reinforcement learning

    Dec 6, 2025Caleb Ju, Guanghui LanPolicy OptimizationRL Exploration

  29. Energy-Based Transfer for Reinforcement Learning

    Jun 19, 2025Zeyun Deng, Jasorsi Ghosh, Fiona Xie +4Transfer Learning in RLTransfer Learning

    ♠Purdue University · ♢AWS AI · ♣Carnegie Mellon University

  30. Ensemble-MIX: Enhancing Sample-Efficiency in Multi-Agent RL via Selective Ensemble-Based Exploration

    Jun 3, 2025Tom Danino, Nahum ShimkinMulti-Agent Reinforcement LearningSample-Efficient RL

    The Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering, Technion- Israel Institute of Technology