{"total":31,"rows":[{"id":"2209.08025","title":"Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability","created":"2022-09-16","cited_by_count":36,"area":null},{"id":"2109.09180","title":"Lifelong Robotic Reinforcement Learning by Retaining Experiences","created":"2021-09-19","cited_by_count":34,"area":null},{"id":"2110.01411","title":"Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey","created":"2021-09-28","cited_by_count":28,"area":null},{"id":"2510.20808","title":"The Reality Gap in Robotics: Challenges, Solutions, and Best Practices","created":"2025-10-23","cited_by_count":24,"area":null},{"id":"2103.03697","title":"Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms","created":"2021-03-05","cited_by_count":22,"area":null},{"id":"2201.08434","title":"DROPO: Sim-to-Real Transfer with Offline Domain Randomization","created":"2022-01-20","cited_by_count":19,"area":null},{"id":"2301.05033","title":"Sim2real Transfer Learning for Point Cloud Segmentation: An Industrial Application Case on Autonomous Disassembly","created":"2023-01-12","cited_by_count":16,"area":null},{"id":"2201.13248","title":"SafeAPT: Safe Simulation-to-Real Robot Learning using Diverse Policies Learned in Simulation","created":"2022-01-27","cited_by_count":10,"area":null},{"id":"2410.01220","title":"Effective Tuning Strategies for Generalist Robot Manipulation Policies","created":"2024-10-02","cited_by_count":10,"area":null},{"id":"2112.03575","title":"MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance","created":"2021-12-07","cited_by_count":8,"area":null},{"id":"2205.05180","title":"Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI","created":"2022-05-10","cited_by_count":6,"area":null},{"id":"2211.08802","title":"Giving Feedback on Interactive Student Programs with Meta-Exploration","created":"2022-11-16","cited_by_count":6,"area":null},{"id":"2109.15233","title":"Solving the Real Robot Challenge using Deep Reinforcement Learning","created":"2021-09-30","cited_by_count":5,"area":null},{"id":"2205.09683","title":"Dexterous Robotic Manipulation using Deep Reinforcement Learning and Knowledge Transfer for Complex Sparse Reward-based Tasks","created":"2022-05-19","cited_by_count":5,"area":null},{"id":"2305.10091","title":"Multi-Agent Reinforcement Learning: Methods, Applications, Visionary Prospects, and Challenges","created":"2023-05-17","cited_by_count":5,"area":null},{"id":"2412.13492","title":"Efficient Language-instructed Skill Acquisition via Reward-Policy Co-Evolution","created":"2024-12-18","cited_by_count":5,"area":null},{"id":"2502.08643","title":"A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards","created":"2025-02-12","cited_by_count":5,"area":null},{"id":"2203.08454","title":"Coach-assisted Multi-Agent Reinforcement Learning Framework for Unexpected Crashed Agents","created":"2022-03-16","cited_by_count":3,"area":null},{"id":"2206.03211","title":"Variational Meta Reinforcement Learning for Social Robotics","created":"2022-06-07","cited_by_count":3,"area":null},{"id":"2312.15474","title":"A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning","created":"2023-12-24","cited_by_count":3,"area":null},{"id":"2503.11007","title":"From Abstraction to Reality: DARPA's Vision for Robust Sim-to-Real Autonomy","created":"2025-03-14","cited_by_count":3,"area":null},{"id":"2307.11357","title":"Bridging the Reality Gap of Reinforcement Learning based Traffic Signal Control using Domain Randomization and Meta Learning","created":"2023-07-21","cited_by_count":2,"area":null},{"id":"2405.18536","title":"Data-Driven Simulator for Mechanical Circulatory Support with Domain Adversarial Neural Process","created":"2024-05-28","cited_by_count":2,"area":null},{"id":"2103.07223","title":"Domain Curiosity: Learning Efficient Data Collection Strategies for Domain Adaptation","created":"2021-03-12","cited_by_count":1,"area":null},{"id":"2112.05299","title":"Zero-Shot Uncertainty-Aware Deployment of Simulation Trained Policies on Real-World Robots","created":"2021-12-10","cited_by_count":1,"area":null},{"id":"2202.08444","title":"A Survey on Deep Reinforcement Learning-based Approaches for Adaptation and Generalization","created":"2022-02-17","cited_by_count":1,"area":null},{"id":"2204.08573","title":"Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models","created":"2022-04-18","cited_by_count":1,"area":null},{"id":"2303.07925","title":"Deep incremental learning models for financial temporal tabular datasets with distribution shifts","created":"2023-03-14","cited_by_count":1,"area":null},{"id":"2506.10133","title":"Statistical Guarantees for Offline Domain Randomization","created":"2025-06-11","cited_by_count":1,"area":null},{"id":"2606.22143","title":"Physics-Informed Eikonal Caging for Whole-Arm Manipulation Planning","created":"2026-06-20","cited_by_count":1,"area":null},{"id":"2207.12248","title":"Domain Adapting Deep Reinforcement Learning for Real-world Speech Emotion Recognition","created":"2022-07-07","cited_by_count":0,"area":null}],"next_cursor":null}