{"total":36,"rows":[{"id":"2005.01643","title":"Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems","created":"2020-05-04","cited_by_count":1920,"area":"offlinerl"},{"id":"2004.07219","title":"D4RL: Datasets for Deep Data-Driven Reinforcement Learning","created":"2020-04-15","cited_by_count":1427,"area":"offlinerl"},{"id":"2005.07648","title":"Language Conditioned Imitation Learning over Unstructured Data","created":"2020-05-15","cited_by_count":209,"area":"offlinerl"},{"id":"1802.09564","title":"Reinforcement and Imitation Learning for Diverse Visuomotor Skills","created":"2018-02-26","cited_by_count":126,"area":"offlinerl"},{"id":"2201.12122","title":"Can Wikipedia Help Offline Reinforcement Learning?","created":"2022-01-28","cited_by_count":77,"area":"offlinerl"},{"id":"1907.13220","title":"Multi-Agent Adversarial Inverse Reinforcement Learning","created":"2019-07-30","cited_by_count":60,"area":"offlinerl"},{"id":"2307.08927","title":"Multi-Stage Cable Routing through Hierarchical Imitation Learning","created":"2023-07-18","cited_by_count":60,"area":"offlinerl"},{"id":"2006.13888","title":"RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning","created":"2020-06-24","cited_by_count":57,"area":"offlinerl"},{"id":"2306.05167","title":"Decision S4: Efficient Sequence-Based RL via State Spaces Layers","created":"2023-06-08","cited_by_count":26,"area":"offlinerl"},{"id":"2210.04688","title":"BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets","created":"2022-10-07","cited_by_count":25,"area":"offlinerl"},{"id":"2210.06692","title":"Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief","created":"2022-10-13","cited_by_count":22,"area":"offlinerl"},{"id":"2111.08857","title":"SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition","created":"2021-11-17","cited_by_count":20,"area":"offlinerl"},{"id":"2111.05440","title":"Dealing with the Unknown: Pessimistic Offline Reinforcement Learning","created":"2021-11-09","cited_by_count":19,"area":"offlinerl"},{"id":"2210.06479","title":"Real World Offline Reinforcement Learning with Realistic Data Source","created":"2022-10-12","cited_by_count":17,"area":"offlinerl"},{"id":"2302.00965","title":"Visual Imitation Learning with Patch Rewards","created":"2023-02-02","cited_by_count":16,"area":"offlinerl"},{"id":"2307.11352","title":"Model-based Offline Reinforcement Learning with Count-based Conservatism","created":"2023-07-21","cited_by_count":16,"area":"offlinerl"},{"id":"2304.04660","title":"Uncertainty-driven Trajectory Truncation for Data Augmentation in Offline Reinforcement Learning","created":"2023-04-10","cited_by_count":13,"area":"offlinerl"},{"id":"2210.00750","title":"Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient","created":"2022-10-03","cited_by_count":12,"area":"offlinerl"},{"id":"2310.01380","title":"Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning","created":"2023-10-02","cited_by_count":9,"area":"offlinerl"},{"id":"2202.01862","title":"Practical Imitation Learning in the Real World via Task Consistency Loss","created":"2022-02-03","cited_by_count":7,"area":"offlinerl"},{"id":"2301.13019","title":"Identifying Expert Behavior in Offline Training Datasets Improves Behavioral Cloning of Robotic Manipulation Policies","created":"2023-01-30","cited_by_count":5,"area":"offlinerl"},{"id":"2203.10905","title":"Self-Imitation Learning from Demonstrations","created":"2022-03-21","cited_by_count":4,"area":"offlinerl"},{"id":"2405.04307","title":"Improving Offline Reinforcement Learning with Inaccurate Simulators","created":"2024-05-07","cited_by_count":4,"area":"offlinerl"},{"id":"2505.16242","title":"Offline Guarded Safe Reinforcement Learning for Medical Treatment Optimization Strategies","created":"2025-05-22","cited_by_count":4,"area":"offlinerl"},{"id":"2101.01052","title":"Imitation Learning for High Precision Peg-in-Hole Tasks","created":"2020-12-26","cited_by_count":3,"area":"offlinerl"},{"id":"2008.01205","title":"Concurrent Training Improves the Performance of Behavioral Cloning from Observation","created":"2020-08-03","cited_by_count":2,"area":"offlinerl"},{"id":"2301.09157","title":"Immersive Demonstrations are the Key to Imitation Learning","created":"2023-01-22","cited_by_count":2,"area":"offlinerl"},{"id":"2303.04016","title":"Decoupling Skill Learning from Robotic Control for Generalizable Object Manipulation","created":"2023-03-07","cited_by_count":2,"area":"offlinerl"},{"id":"2303.16427","title":"Learning Excavation of Rigid Objects with Offline Reinforcement Learning","created":"2023-03-29","cited_by_count":2,"area":"offlinerl"},{"id":"2508.14379","title":"Action-Constrained Imitation Learning","created":"2025-08-20","cited_by_count":2,"area":"offlinerl"},{"id":"2505.12211","title":"Imagination-Limited Q-Learning for Offline Reinforcement Learning","created":"2025-05-18","cited_by_count":1,"area":"offlinerl"},{"id":"2111.08156","title":"Improving Learning from Demonstrations by Learning from Experience","created":"2021-11-16","cited_by_count":0,"area":"offlinerl"},{"id":"2208.00478","title":"Robot Policy Learning from Demonstration Using Advantage Weighting and Early Termination","created":"2022-07-31","cited_by_count":0,"area":"offlinerl"},{"id":"2310.00489","title":"Interpretable Imitation Learning with Dynamic Causal Relations","created":"2023-09-30","cited_by_count":0,"area":"offlinerl"},{"id":"2606.19752","title":"Temporal Self-Imitation Learning","created":"2026-06-18","cited_by_count":0,"area":"offlinerl"},{"id":"2609.13234","title":"Harnessing human expertise for high-precision robotic assembly in industrialized construction: A sample-efficient installer-in-the-loop interactive reinforcement learning framework","created":"2026-09-02","cited_by_count":0,"area":"offlinerl"}],"next_cursor":null}