{"total":19,"rows":[{"id":"2305.11997","title":"Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees","created":"2023-05-19","cited_by_count":45,"area":null},{"id":"2305.00241","title":"When Deep Learning Meets Polyhedral Theory: A Survey","created":"2023-04-29","cited_by_count":39,"area":null},{"id":"2402.01928","title":"Robust Counterfactual Explanations in Machine Learning: A Survey","created":"2024-02-02","cited_by_count":29,"area":null},{"id":"2309.12545","title":"Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation","created":"2023-09-22","cited_by_count":20,"area":null},{"id":"2304.12943","title":"Generating robust counterfactual explanations","created":"2023-04-24","cited_by_count":13,"area":null},{"id":"2408.04842","title":"Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change","created":"2024-08-09","cited_by_count":10,"area":null},{"id":"2307.02131","title":"Beyond Known Reality: Exploiting Counterfactual Explanations for Medical Research","created":"2023-07-05","cited_by_count":9,"area":null},{"id":"2404.13736","title":"Interval Abstractions for Robust Counterfactual Explanations","created":"2024-04-21","cited_by_count":7,"area":null},{"id":"2401.14086","title":"Generating Likely Counterfactuals Using Sum-Product Networks","created":"2024-01-25","cited_by_count":6,"area":null},{"id":"2503.07934","title":"Counterfactual Explanations for Model Ensembles Using Entropic Risk Measures","created":"2025-03-11","cited_by_count":5,"area":null},{"id":"2402.11168","title":"Trust Regions for Explanations via Black-Box Probabilistic Certification","created":"2024-02-17","cited_by_count":4,"area":null},{"id":"2403.11642","title":"Guiding the generation of counterfactual explanations through temporal background knowledge for Predictive Process Monitoring","created":"2024-03-18","cited_by_count":3,"area":null},{"id":"2411.04855","title":"Clinicians' Voice: Fundamental Considerations for XAI in Healthcare","created":"2024-11-07","cited_by_count":3,"area":null},{"id":"2503.01792","title":"Generating Counterfactual Explanations Under Temporal Constraints","created":"2025-03-03","cited_by_count":3,"area":null},{"id":"2602.09748","title":"Linear Model Extraction via Factual and Counterfactual Queries","created":"2026-02-10","cited_by_count":2,"area":null},{"id":"2303.11111","title":"Iterative Partial Fulfillment of Counterfactual Explanations: Benefits and Risks","created":"2023-03-17","cited_by_count":1,"area":null},{"id":"2502.16380","title":"Understanding Fixed Predictions via Confined Regions","created":"2025-02-22","cited_by_count":1,"area":null},{"id":"2602.08021","title":"Structure-Aware Robust Counterfactual Explanations via Conditional Gaussian Network Classifiers","created":"2026-02-08","cited_by_count":0,"area":null},{"id":"2604.09573","title":"Improving understanding and trust in AI: How users benefit from interval-based counterfactual explanations","created":"2026-02-22","cited_by_count":0,"area":null}],"next_cursor":null}