{"total":26,"rows":[{"id":"2210.11584","title":"Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations","created":"2022-10-20","cited_by_count":85,"area":null},{"id":"2101.12446","title":"Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep Learning","created":"2021-01-29","cited_by_count":39,"area":null},{"id":"2301.09937","title":"Explainable Deep Reinforcement Learning: State of the Art and Challenges","created":"2023-01-24","cited_by_count":33,"area":null},{"id":"2108.09003","title":"Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey","created":"2021-08-20","cited_by_count":24,"area":null},{"id":"2105.02658","title":"Explainable Autonomous Robots: A Survey and Perspective","created":"2021-05-06","cited_by_count":15,"area":null},{"id":"2312.11118","title":"Explaining Reinforcement Learning Agents Through Counterfactual Action Outcomes","created":"2023-12-18","cited_by_count":14,"area":null},{"id":"2301.00901","title":"Towards Modeling and Influencing the Dynamics of Human Learning","created":"2023-01-02","cited_by_count":11,"area":null},{"id":"2210.11825","title":"Integrating Policy Summaries with Reward Decomposition for Explaining Reinforcement Learning Agents","created":"2022-10-21","cited_by_count":10,"area":null},{"id":"2102.03064","title":"\"I Don't Think So\": Summarizing Policy Disagreements for Agent Comparison","created":"2021-02-05","cited_by_count":6,"area":null},{"id":"2202.11296","title":"Reinforcement Learning in Practice: Opportunities and Challenges","created":"2022-02-23","cited_by_count":6,"area":null},{"id":"2112.09462","title":"Contrastive Explanations for Comparing Preferences of Reinforcement Learning Agents","created":"2021-12-17","cited_by_count":5,"area":null},{"id":"2110.04192","title":"Explaining Reward Functions to Humans for Better Human-Robot Collaboration","created":"2021-10-08","cited_by_count":3,"area":null},{"id":"2310.07802","title":"An Information Bottleneck Characterization of the Understanding-Workload Tradeoff","created":"2023-10-11","cited_by_count":3,"area":null},{"id":"2201.07749","title":"Summarising and Comparing Agent Dynamics with Contrastive Spatiotemporal Abstraction","created":"2022-01-17","cited_by_count":2,"area":null},{"id":"2206.01306","title":"Deceptive Planning for Resource Allocation","created":"2022-06-02","cited_by_count":2,"area":null},{"id":"2208.08552","title":"A Framework for Understanding and Visualizing Strategies of RL Agents","created":"2022-08-17","cited_by_count":2,"area":null},{"id":"2209.09141","title":"\"Guess what I'm doing\": Extending legibility to sequential decision tasks","created":"2022-09-19","cited_by_count":2,"area":null},{"id":"2211.07719","title":"(When) Are Contrastive Explanations of Reinforcement Learning Helpful?","created":"2022-11-14","cited_by_count":1,"area":null},{"id":"2312.12102","title":"I-CEE: Tailoring Explanations of Image Classification Models to User Expertise","created":"2023-12-19","cited_by_count":1,"area":null},{"id":"2211.06376","title":"Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning","created":"2022-11-11","cited_by_count":0,"area":null},{"id":"2301.09941","title":"ASQ-IT: Interactive Explanations for Reinforcement-Learning Agents","created":"2023-01-24","cited_by_count":0,"area":null},{"id":"2304.00367","title":"Conveying Autonomous Robot Capabilities through Contrasting Behaviour Summaries","created":"2023-04-01","cited_by_count":0,"area":null},{"id":"2307.08933","title":"IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit based on Analyses of Interestingness","created":"2023-07-18","cited_by_count":0,"area":null},{"id":"2406.11850","title":"Closed-loop Teaching via Demonstrations to Improve Policy Transparency","created":"2024-04-01","cited_by_count":0,"area":null},{"id":"2504.04592","title":"\"Trust me on this\" Explaining Agent Behavior to a Human Terminator","created":"2025-04-06","cited_by_count":0,"area":null},{"id":"2605.22986","title":"Robots That Know What to Ask: Recovering Misaligned Rewards through Targeted Explanations","created":"2026-05-21","cited_by_count":0,"area":null}],"next_cursor":null}