{"total":17,"rows":[{"id":"2103.14651","title":"Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice","created":"2021-03-27","cited_by_count":45,"area":null},{"id":"2205.09696","title":"Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging","created":"2022-05-19","cited_by_count":32,"area":null},{"id":"2302.06503","title":"Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making","created":"2023-02-13","cited_by_count":25,"area":null},{"id":"2302.01928","title":"Aligning Robot and Human Representations","created":"2023-02-03","cited_by_count":11,"area":null},{"id":"2108.04219","title":"Pragmatic Image Compression for Human-in-the-Loop Decision-Making","created":"2021-07-07","cited_by_count":7,"area":null},{"id":"2205.06905","title":"Perspectives on Incorporating Expert Feedback into Model Updates","created":"2022-05-13","cited_by_count":7,"area":null},{"id":"2502.13062","title":"AI-Assisted Decision Making with Human Learning","created":"2025-02-18","cited_by_count":6,"area":null},{"id":"2503.17482","title":"What's Producible May Not Be Reachable: Measuring the Steerability of Generative Models","created":"2025-03-21","cited_by_count":6,"area":null},{"id":"2102.03977","title":"Learning to Generate Fair Clusters from Demonstrations","created":"2021-02-08","cited_by_count":4,"area":null},{"id":"2205.07333","title":"Trucks Don't Mean Trump: Diagnosing Human Error in Image Analysis","created":"2022-05-15","cited_by_count":4,"area":null},{"id":"2206.05981","title":"Efficient Human-in-the-loop System for Guiding DNNs Attention","created":"2022-06-13","cited_by_count":4,"area":null},{"id":"2306.10606","title":"Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces","created":"2023-06-18","cited_by_count":3,"area":null},{"id":"2112.03799","title":"A pragmatic account of the weak evidence effect","created":"2021-12-07","cited_by_count":2,"area":null},{"id":"2406.00116","title":"A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning","created":"2024-05-31","cited_by_count":2,"area":null},{"id":"2106.14384","title":"Towards Model-informed Precision Dosing with Expert-in-the-loop Machine Learning","created":"2021-06-28","cited_by_count":0,"area":null},{"id":"2602.19620","title":"Rules or Weights? Comparing User Understanding of Explainable AI Techniques with the Cognitive XAI-Adaptive Model","created":"2026-02-23","cited_by_count":0,"area":null},{"id":"2604.27354","title":"CoAX: Cognitive-Oriented Attribution eXplanation User Model of Human Understanding of AI Explanations","created":"2026-04-30","cited_by_count":0,"area":null}],"next_cursor":null}