{"total":40,"rows":[{"id":"2112.11313","title":"On the Adversarial Robustness of Causal Algorithmic Recourse","created":"2021-12-21","cited_by_count":56,"area":null},{"id":"2207.14526","title":"Leveraging Explanations in Interactive Machine Learning: An Overview","created":"2022-07-29","cited_by_count":53,"area":null},{"id":"2203.06768","title":"Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse","created":"2022-03-13","cited_by_count":40,"area":null},{"id":"2201.09051","title":"On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations","created":"2022-01-22","cited_by_count":32,"area":null},{"id":"2208.14137","title":"On the Trade-Off between Actionable Explanations and the Right to be Forgotten","created":"2022-08-30","cited_by_count":20,"area":null},{"id":"2210.12051","title":"The privacy issue of counterfactual explanations: explanation linkage attacks","created":"2022-10-21","cited_by_count":20,"area":null},{"id":"2301.11113","title":"Finding Regions of Counterfactual Explanations via Robust Optimization","created":"2023-01-26","cited_by_count":19,"area":null},{"id":"2304.12943","title":"Generating robust counterfactual explanations","created":"2023-04-24","cited_by_count":13,"area":null},{"id":"2302.03465","title":"Robustness Implies Fairness in Causal Algorithmic Recourse","created":"2023-02-07","cited_by_count":12,"area":null},{"id":"2205.05515","title":"Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting","created":"2022-05-11","cited_by_count":11,"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":"2205.03398","title":"Let's Go to the Alien Zoo: Introducing an Experimental Framework to Study Usability of Counterfactual Explanations for Machine Learning","created":"2022-05-06","cited_by_count":9,"area":null},{"id":"2211.14858","title":"\"Explain it in the Same Way!\" -- Model-Agnostic Group Fairness of Counterfactual Explanations","created":"2022-11-27","cited_by_count":9,"area":null},{"id":"2306.00497","title":"The Risks of Recourse in Binary Classification","created":"2023-06-01","cited_by_count":8,"area":null},{"id":"2410.08007","title":"Time Can Invalidate Algorithmic Recourse","created":"2024-10-10","cited_by_count":8,"area":null},{"id":"2309.04676","title":"Flexible and Robust Counterfactual Explanations with Minimal Satisfiable Perturbations","created":"2023-09-09","cited_by_count":6,"area":null},{"id":"2401.14086","title":"Generating Likely Counterfactuals Using Sum-Product Networks","created":"2024-01-25","cited_by_count":6,"area":null},{"id":"2211.04780","title":"On the Robustness of Explanations of Deep Neural Network Models: A Survey","created":"2022-11-09","cited_by_count":5,"area":null},{"id":"2312.10648","title":"Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals","created":"2023-12-17","cited_by_count":5,"area":null},{"id":"2403.01221","title":"A Two-Stage Algorithm for Cost-Efficient Multi-instance Counterfactual Explanations","created":"2024-03-02","cited_by_count":5,"area":null},{"id":"2306.07637","title":"For Better or Worse: The Impact of Counterfactual Explanations' Directionality on User Behavior in xAI","created":"2023-06-13","cited_by_count":4,"area":null},{"id":"2407.08497","title":"CE-QArg: Counterfactual Explanations for Quantitative Bipolar Argumentation Frameworks (Technical Report)","created":"2024-07-11","cited_by_count":3,"area":null},{"id":"2412.09376","title":"A comprehensive interpretable machine learning framework for Mild Cognitive Impairment and Alzheimer's disease diagnosis","created":"2024-12-12","cited_by_count":3,"area":null},{"id":"2407.11426","title":"Generally-Occurring Model Change for Robust Counterfactual Explanations","created":"2024-07-16","cited_by_count":2,"area":null},{"id":"2512.14559","title":"Counterfactual Explanations for Time Series Should be Human-Centered and Temporally Coherent in Interventions","created":"2025-12-16","cited_by_count":2,"area":null},{"id":"2601.20449","title":"Fair Recourse for All: Ensuring Individual and Group Fairness in Counterfactual Explanations","created":"2026-01-28","cited_by_count":2,"area":null},{"id":"2303.04579","title":"\"How to make them stay?\" -- Diverse Counterfactual Explanations of Employee Attrition","created":"2023-03-08","cited_by_count":1,"area":null},{"id":"2309.16146","title":"T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems","created":"2023-09-28","cited_by_count":1,"area":null},{"id":"2402.04579","title":"Collective Counterfactual Explanations: Balancing Individual Goals and Collective Dynamics","created":"2024-02-07","cited_by_count":1,"area":null},{"id":"2407.11089","title":"Explainable bank failure prediction models: Counterfactual explanations to reduce the failure risk","created":"2024-07-14","cited_by_count":1,"area":null},{"id":"2408.06679","title":"Case-based Explainability for Random Forest: Prototypes, Critics, Counter-factuals and Semi-factuals","created":"2024-08-13","cited_by_count":1,"area":null},{"id":"2410.15723","title":"S-CFE: Simple Counterfactual Explanations","created":"2024-10-21","cited_by_count":1,"area":null},{"id":"2509.19921","title":"On the Fragility of Contribution Score Computation in Federated Learning","created":"2025-09-24","cited_by_count":1,"area":null},{"id":"2510.04855","title":"Synthesising Counterfactual Explanations via Label-Conditional Gaussian Mixture Variational Autoencoders","created":"2025-10-06","cited_by_count":1,"area":null},{"id":"2212.05256","title":"Causality-Aware Local Interpretable Model-Agnostic Explanations","created":"2022-12-10","cited_by_count":0,"area":null},{"id":"2406.03012","title":"Towards Understanding the Influence of Training Samples on Explanations","created":"2024-06-05","cited_by_count":0,"area":null},{"id":"2601.09455","title":"On the Hardness of Computing Counterfactual and Semifactual Explanations in XAI","created":"2026-01-14","cited_by_count":0,"area":null},{"id":"2602.00063","title":"The Impact of Machine Learning Uncertainty on the Robustness of Counterfactual Explanations","created":"2026-01-20","cited_by_count":0,"area":null},{"id":"2606.16786","title":"We Need Explanation Cards to Connect Explanation Algorithms to the Real World","created":"2026-06-15","cited_by_count":0,"area":null},{"id":"2606.18832","title":"Target-confidence Recourse Using tSeTlin machines: TRUST","created":"2026-06-17","cited_by_count":0,"area":null}],"next_cursor":null}