{"total":24,"rows":[{"id":"2102.13076","title":"Benchmarking and Survey of Explanation Methods for Black Box Models","created":"2021-02-25","cited_by_count":136,"area":null},{"id":"2102.03322","title":"CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks","created":"2021-02-05","cited_by_count":119,"area":null},{"id":"2103.01035","title":"If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques","created":"2021-02-26","cited_by_count":82,"area":null},{"id":"2207.02739","title":"Robust Counterfactual Explanations for Tree-Based Ensembles","created":"2022-07-06","cited_by_count":49,"area":null},{"id":"2305.11997","title":"Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees","created":"2023-05-19","cited_by_count":45,"area":null},{"id":"2106.06631","title":"Optimal Counterfactual Explanations in Tree Ensembles","created":"2021-06-11","cited_by_count":36,"area":null},{"id":"2305.17021","title":"GLOBE-CE: A Translation-Based Approach for Global Counterfactual Explanations","created":"2023-05-26","cited_by_count":27,"area":null},{"id":"2208.14878","title":"Formalising the Robustness of Counterfactual Explanations for Neural Networks","created":"2022-08-31","cited_by_count":24,"area":null},{"id":"2110.14270","title":"Counterfactual Shapley Additive Explanations","created":"2021-10-27","cited_by_count":22,"area":null},{"id":"2107.04680","title":"A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data","created":"2021-07-09","cited_by_count":19,"area":null},{"id":"2108.08197","title":"CARE: Coherent Actionable Recourse based on Sound Counterfactual Explanations","created":"2021-08-18","cited_by_count":17,"area":null},{"id":"2107.09734","title":"Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions","created":"2021-07-20","cited_by_count":16,"area":null},{"id":"2212.08733","title":"Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ","created":"2022-12-16","cited_by_count":12,"area":null},{"id":"2401.03451","title":"Optimization Over Trained Neural Networks: Taking a Relaxing Walk","created":"2024-01-07","cited_by_count":10,"area":null},{"id":"2204.06917","title":"Global Counterfactual Explanations: Investigations, Implementations and Improvements","created":"2022-04-14","cited_by_count":9,"area":null},{"id":"2310.12822","title":"Generating collective counterfactual explanations in score-based classification via mathematical optimization","created":"2023-10-19","cited_by_count":9,"area":null},{"id":"2209.10997","title":"Counterfactual Explanations Using Optimization With Constraint Learning","created":"2022-09-22","cited_by_count":8,"area":null},{"id":"2301.10074","title":"Explainable Data-Driven Optimization: From Context to Decision and Back Again","created":"2023-01-24","cited_by_count":7,"area":null},{"id":"2406.01098","title":"Learning Decision Trees and Forests with Algorithmic Recourse","created":"2024-06-03","cited_by_count":7,"area":null},{"id":"2301.08833","title":"Bayesian Hierarchical Models for Counterfactual Estimation","created":"2023-01-21","cited_by_count":6,"area":null},{"id":"2312.16699","title":"Computational Tradeoffs of Optimization-Based Bound Tightening in ReLU Networks","created":"2023-12-27","cited_by_count":6,"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":"2405.20664","title":"Weak Robust Compatibility Between Learning Algorithms and Counterfactual Explanation Generation Algorithms","created":"2024-05-31","cited_by_count":1,"area":null},{"id":"2311.07797","title":"Explainable History Distillation by Marked Temporal Point Process","created":"2023-11-13","cited_by_count":0,"area":null}],"next_cursor":null}