Offline RL

RL: Reinforcement Learning

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29 papers in the last four weeks, up 222% on the four weeks before. 0.3% of all new papers.

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Evaluating covariate balance for long time horizon Markov decision processes
Jul 16, 2026Joshua Spear, Rebecca Pope, Neil J SebireCausal Effect Estimation Reinforcement Learning
UCL GOS Institute of Child Health · NIHR GOSH UCL BRC
RENEW: Towards Learning World Models and Repairing Model Exploitation from Preferences
Jul 15, 2026Logan Mondal Bhamidipaty, Mykel Kochenderfer, Subramanian RamamoorthyWorld Model Learning Offline RL
University of Edinburgh · 2Stanford University
Active Offline-to-Online Reinforcement Learning
Jul 13, 2026Alper Kamil Bozkurt, Shangtong Zhang, Yuichi MotaiOffline RL RL Fine-Tuning
Virginia Commonwealth University, USA · University of Virginia, USA
VINE: Taming Generative Control Policies for Reinforcement Learning
Jul 11, 2026Rushuai Yang, Zhuo Han, Houlin Li +10RL for Robotics Offline RL
1AgiBot · 3Peking University · 2The Hong Kong University of Science and Technology
Shortcut Trajectory Planning for Efficient Offline Reinforcement Learning
Jul 10, 2026Guanquan Wang, Yoshimasa TsuruokaTrajectory Generation Offline RL
Department of Information and Communication Engineering · The University of Tokyo
NFTR: From Provable Mode-Averaging to Geodesic Subgoal Selection in Offline Goal-Conditioned RL
Jul 8, 2026Erdemt Bao, Xing Lei, Jun Chen +2Normalizing Flows Hierarchical RL
Huazhong University of Science and Technology · Xi’an Jiaotong University · University of Electronic Science and Technology of China
Fitted Occupancy-Ratio Evaluation without Bellman Completeness
Jul 6, 2026Lars van der Laan, Nathan KallusOff-Policy Evaluation Offline RL
Stanford University · Netflix · Cornell University
Learning to Control LLM Agent Harnesses with Offline Reinforcement Learning
Jul 5, 2026Haiwen Yi, Xinyuan SongOffline RL LLM Agent Harnesses
University of Toronto · Emory University
CDCP: Conditional Diffusion Model with Contextual Prompts for Multi-task Offline Safe Reinforcement Learning
Jul 4, 2026Jiayi Guan, Tianle Zhang, Li Shen +8Reinforcement Learning Constrained RL
Tongji University, Shanghai, China · JD Explore Academy, Beijing, China · School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China +2
A Hierarchy of Policy Learning Problems
Jul 3, 2026Hamsa Bastani, Osbert Bastani, Shihan ChenSample Complexity Offline RL
Wharton School, University of Pennsylvania · University of Pennsylvania · Graduate Group in Applied Mathematics and Computational Science, University of Pennsylvania
Generalization in offline RL: The structure is more important than the amount of pessimism
Jul 2, 2026Max Weltevrede, Matthijs T. J. Spaan, Wendelin BöhmerReinforcement Learning Offline RL
Delft University of Technology, Delft, The Netherlands
SPLC: Social Preference Learning for Crowd Robot Navigation
Jul 2, 2026Zixuan Chen, Hao Fu, Haiwen Hu +1Robot Navigation Social Robot Navigation
Wuhan University of Science and Technology, Wuhan, China · School of Computer Science and Technology, Wuhan University of Science and Technology and also with the Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan 430081, China
AETDICE: Unified Framework and Offline Optimization for Nonlinear Multi-Objective RL
Jun 30, 2026Woosung Kim, Youngjun Suh, Jinho Lee +2Multi-Objective Reinforcement Learning Offline RL
1Korea University · 2Yonsei University · 3Gauss Labs Inc.
Offline Reinforcement Learning for Fluid Controls: Data-based Multi-observational Policy Extraction
Jun 30, 2026Deepak Akhare, Luning Sun, Xin-Yang Liu +4RL Control Reinforcement Learning
Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN · Lawrence Livermore National Laboratory, University of Notre Dame, Livermore, CA · Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA
Pessimism's Paradox: Conservative Offline Training Amplifies Reward Hacking During Online Adaptation in Reasoning Models
Jun 29, 2026Subramanyam Sahoo, Aman Chadha, Vinija Jain +1Reward Modeling Reward Hacking
1Horizon Research · 2Apple · 3Meta +1
STEAM: Self-Supervised Temporal Ensemble Advantage Modeling for Real-World Robot Learning
Jun 29, 2026Zhihao Liu, Qiuyi Gu, Yitao Wang +16Robot Policy Learning Robot Skill Learning
Institute of Automation, Chinese Academy of Sciences · School of Artificial Intelligence, University of Chinese Academy of Sciences · Zhongguancun Academy +8
RS-Diffuser: Risk-Sensitive Diffusion Planning with Distributional Value Guidance
Jun 26, 2026Shiqiang GongDistributional RL Diffusion-Based Planning
Northwestern Polytechnical University
Offline Multi-agent Continual Cooperation via Skill Partition and Reuse
Jun 24, 2026Yuchen Xiao, Lei Yuan, Ruiqi Xue +2Offline RL Agent Skill Learning
National Key Laboratory for Novel Software Technology, Nanjing University · School of Artificial Intelligence, Nanjing University · Polixir Technologies +1
Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models
Jun 23, 2026Thibaut KulakReinforcement Learning Transformer
NeoInstinct SA
Offline Reinforcement Learning for Warehouse SLAM Throughput Control
Jun 22, 2026Tina Dongxu Li, Mouhacine Benosman, Rajat Kumar +3RL Control Offline RL
Amazon.com, USA
Weight-Space Geometry of Offline Reasoning Training
Jun 21, 2026Aleksandr Nikolich, Igor Kiselev, Vladimir Platonov +1RL for Language Models Direct Preference Optimization
1Keenable AI · 2Accenture · 3Yandex
Horizon Adaptive Offline Policy Learning via Value Stitching
Jun 19, 2026Kexin Zheng, Xianyuan Zhan, Xintao YanValue Function Estimation Offline RL
The University of Hong Kong · Tsinghua University
Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random
Jun 18, 2026Ziheng Wei, Annie Qu, Rui MiaoReinforcement Learning Off-Policy Evaluation
Department of Statistics, University of Michigan at Ann Arbor · Department of Statistics and Applied Probability, University of California at Santa Barbara · Department of Mathematical Sciences, University of Texas at Dallas
Insulin4RL: Real-Time Insulin Management in the Intensive Care Unit for Offline Reinforcement Learning
Jun 17, 2026Thomas Frost, Steve HarrisRL Benchmarks Offline RL
Institute of Health Informatics University College London London, United Kingdom
Wasserstein Policy Learning for Distributional Outcomes
Jun 17, 2026Yiyan Huang, Cheuk Hang Leung, Qi Wu +1Offline RL Wasserstein Barycenters
School of Statistics and Data Science & Institute of Big Data Research, Shanghai University of Finance and Economics, Shanghai, China
When Does Trajectory-Level Supervision Permit Efficient Offline Reinforcement Learning?
Jun 16, 2026Xuanfei Ren, Tengyang XieOffline RL
University of Wisconsin-Madison · Madison, WI
Reversal Q-Learning
Jun 16, 2026Aditya Oberai, Seohong Park, Sergey LevineReinforcement Learning Q-Learning
University of California, Berkeley.
Video-Based Optimal Transport for Feedback-Efficient Offline Preference-Based Reinforcement Learning
Jun 15, 2026Tung M. Luu, Hwanhee Kim, Younghwan Lee +1Offline RL Semi-Supervised Learning
Korea Advanced Institute of Science and Technology (KAIST).
Diffusion Offline Reinforcement Learning for Fair and Energy-Efficient UAV-Assisted Wireless Networks
Jun 15, 2026Eslam Eldeeb, Hirley AlvesOffline RL Wireless Communications
Centre for Wireless Communications (CWC), University of Oulu, Finland
DRIVE: Distributional and Retrieval-Augmented Bidding with Value Evaluation
Jun 12, 2026Miduo Cui, Haochen Wang, Shangqin Mao +6Distributional RL Automated Bidding
Shandong University, Jinan, China · Meituan, Beijing, China

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Evaluating covariate balance for long time horizon Markov decision processes

Joshua Spear, Rebecca Pope, Neil J Sebire

UCL GOS Institute of Child Health · NIHR GOSH UCL BRC

Causal Effect Estimation Reinforcement Learning Offline RL

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This article explores the application of covariate balance diagnostics for detecting the presence of hidden confounding/model miss-specification in studies applying offline reinforcement learning (RL) to deriving optimal treatment recommendations. The results demonstrate that, either there is a high risk of bias within existing offline RL studies for treatment recommendations or, existing covariate balance metrics are not sufficient to assess such studies. Regardless, existing offline RL studies cannot be concluded as being statistically robust. The conclusions propose future research directions for obtaining more methodologically robust applications of offline RL to treatment recommendation problems.

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