{"total":127,"rows":[{"id":"2110.01889","title":"Deep Neural Networks and Tabular Data: A Survey","created":"2021-10-05","cited_by_count":491,"area":null},{"id":"2108.00783","title":"CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms","created":"2021-08-02","cited_by_count":86,"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":"2104.07411","title":"NICE: An Algorithm for Nearest Instance Counterfactual Explanations","created":"2021-04-15","cited_by_count":62,"area":null},{"id":"2103.01826","title":"Strategic Classification Made Practical","created":"2021-03-02","cited_by_count":59,"area":null},{"id":"2112.11313","title":"On the Adversarial Robustness of Causal Algorithmic Recourse","created":"2021-12-21","cited_by_count":56,"area":null},{"id":"2103.11972","title":"Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals","created":"2021-03-22","cited_by_count":55,"area":null},{"id":"2106.09992","title":"Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis","created":"2021-06-18","cited_by_count":52,"area":null},{"id":"2103.08951","title":"Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties","created":"2021-03-16","cited_by_count":41,"area":null},{"id":"2105.15164","title":"DISSECT: Disentangled Simultaneous Explanations via Concept Traversals","created":"2021-05-31","cited_by_count":37,"area":null},{"id":"2110.03109","title":"Consistent Counterfactuals for Deep Models","created":"2021-10-06","cited_by_count":37,"area":null},{"id":"2203.15064","title":"Cycle-Consistent Counterfactuals by Latent Transformations","created":"2022-03-28","cited_by_count":33,"area":null},{"id":"2205.06504","title":"DualCF: Efficient Model Extraction Attack from Counterfactual Explanations","created":"2022-05-13","cited_by_count":32,"area":null},{"id":"2206.05075","title":"Diffeomorphic Counterfactuals with Generative Models","created":"2022-06-10","cited_by_count":29,"area":null},{"id":"2101.10123","title":"Conditional Generative Models for Counterfactual Explanations","created":"2021-01-25","cited_by_count":28,"area":null},{"id":"2108.13025","title":"Transport-based Counterfactual Models","created":"2021-08-30","cited_by_count":27,"area":null},{"id":"2106.00461","title":"To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods","created":"2021-06-01","cited_by_count":26,"area":null},{"id":"2106.03962","title":"Amortized Generation of Sequential Algorithmic Recourses for Black-box Models","created":"2021-06-07","cited_by_count":24,"area":null},{"id":"2202.12451","title":"Human-Centered Concept Explanations for Neural Networks","created":"2022-02-25","cited_by_count":23,"area":null},{"id":"2304.01391","title":"Counterfactual Learning on Graphs: A Survey","created":"2023-04-03","cited_by_count":22,"area":null},{"id":"2205.15834","title":"Attribution-based Explanations that Provide Recourse Cannot be Robust","created":"2022-05-31","cited_by_count":20,"area":null},{"id":"2208.14966","title":"Concept Gradient: Concept-based Interpretation Without Linear Assumption","created":"2022-08-31","cited_by_count":20,"area":null},{"id":"2403.09683","title":"Counterfactual Image Editing","created":"2024-02-07","cited_by_count":20,"area":null},{"id":"2109.01904","title":"Estimating Categorical Counterfactuals via Deep Twin Networks","created":"2021-09-04","cited_by_count":19,"area":null},{"id":"2106.07754","title":"Counterfactual Explanations as Interventions in Latent Space","created":"2021-06-14","cited_by_count":18,"area":null},{"id":"2206.04101","title":"What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective","created":"2022-06-08","cited_by_count":18,"area":null},{"id":"2104.05592","title":"Consequence-aware Sequential Counterfactual Generation","created":"2021-04-12","cited_by_count":17,"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":"2109.07557","title":"CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations","created":"2021-09-15","cited_by_count":17,"area":null},{"id":"2204.10152","title":"Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI","created":"2022-04-21","cited_by_count":16,"area":null},{"id":"2211.00472","title":"Backtracking Counterfactuals","created":"2022-11-01","cited_by_count":16,"area":null},{"id":"2106.02597","title":"Model-agnostic and Scalable Counterfactual Explanations via Reinforcement Learning","created":"2021-06-04","cited_by_count":15,"area":null},{"id":"2112.06283","title":"Bayesian Persuasion for Algorithmic Recourse","created":"2021-12-12","cited_by_count":14,"area":null},{"id":"2302.03225","title":"Efficient XAI Techniques: A Taxonomic Survey","created":"2023-02-07","cited_by_count":14,"area":null},{"id":"2205.05306","title":"The Conflict Between Explainable and Accountable Decision-Making Algorithms","created":"2022-05-11","cited_by_count":13,"area":null},{"id":"2208.02878","title":"Differentially Private Counterfactuals via Functional Mechanism","created":"2022-08-04","cited_by_count":13,"area":null},{"id":"2210.11846","title":"Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities","created":"2022-10-21","cited_by_count":13,"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":"2307.00364","title":"The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations","created":"2023-07-01","cited_by_count":12,"area":null},{"id":"2111.01235","title":"Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions","created":"2021-11-01","cited_by_count":10,"area":null},{"id":"2302.14165","title":"GAM Coach: Towards Interactive and User-centered Algorithmic Recourse","created":"2023-02-27","cited_by_count":9,"area":null},{"id":"2303.09297","title":"Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals","created":"2023-03-16","cited_by_count":9,"area":null},{"id":"2308.08187","title":"Endogenous Macrodynamics in Algorithmic Recourse","created":"2023-08-16","cited_by_count":9,"area":null},{"id":"2309.04470","title":"On the Actionability of Outcome Prediction","created":"2023-09-08","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":"2411.02259","title":"Counterfactual Explanations via Riemannian Latent Space Traversal","created":"2024-11-04","cited_by_count":9,"area":null},{"id":"2109.04518","title":"Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation","created":"2021-09-09","cited_by_count":8,"area":null},{"id":"2306.00497","title":"The Risks of Recourse in Binary Classification","created":"2023-06-01","cited_by_count":8,"area":null},{"id":"2410.10463","title":"TABCF: Counterfactual Explanations for Tabular Data Using a Transformer-Based VAE","created":"2024-10-14","cited_by_count":8,"area":null},{"id":"2111.09790","title":"MCCE: Monte Carlo sampling of realistic counterfactual explanations","created":"2021-11-18","cited_by_count":7,"area":null},{"id":"2605.11161","title":"Interpretability Can Be Actionable","created":"2026-05-11","cited_by_count":7,"area":null},{"id":"2111.15639","title":"DeDUCE: Generating Counterfactual Explanations Efficiently","created":"2021-11-29","cited_by_count":6,"area":null},{"id":"2302.11213","title":"Feasible Recourse Plan via Diverse Interpolation","created":"2023-02-22","cited_by_count":6,"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":"2112.00890","title":"Counterfactual Explanations via Latent Space Projection and Interpolation","created":"2021-12-02","cited_by_count":5,"area":null},{"id":"2206.14384","title":"Framing Algorithmic Recourse for Anomaly Detection","created":"2022-06-29","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":"2402.09702","title":"Sparse and Faithful Explanations Without Sparse Models","created":"2024-02-15","cited_by_count":5,"area":null},{"id":"2404.03506","title":"CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forests","created":"2024-04-04","cited_by_count":5,"area":null},{"id":"2505.07351","title":"From Search To Sampling: Generative Models For Robust Algorithmic Recourse","created":"2025-05-12","cited_by_count":5,"area":null},{"id":"2207.01917","title":"GLANCE: Global to Local Architecture-Neutral Concept-based Explanations","created":"2022-07-05","cited_by_count":4,"area":null},{"id":"2210.17071","title":"Computing Rule-Based Explanations by Leveraging Counterfactuals","created":"2022-10-31","cited_by_count":4,"area":null},{"id":"2306.06325","title":"Explaining a machine learning decision to physicians via counterfactuals","created":"2023-06-10","cited_by_count":4,"area":null},{"id":"2308.07198","title":"Explaining Black-Box Models through Counterfactuals","created":"2023-08-14","cited_by_count":4,"area":null},{"id":"2308.12820","title":"Prediction without Preclusion: Recourse Verification with Reachable Sets","created":"2023-08-24","cited_by_count":4,"area":null},{"id":"2403.09232","title":"Generating Feasible and Plausible Counterfactual Explanations for Outcome Prediction of Business Processes","created":"2024-03-14","cited_by_count":4,"area":null},{"id":"2410.01580","title":"Learning-Augmented Robust Algorithmic Recourse","created":"2024-10-02","cited_by_count":4,"area":null},{"id":"2102.06362","title":"A Decentralized Approach towards Responsible AI in Social Ecosystems","created":"2021-02-12","cited_by_count":3,"area":null},{"id":"2501.08850","title":"Graph Counterfactual Explainable AI via Latent Space Traversal","created":"2025-01-15","cited_by_count":3,"area":null},{"id":"2506.00832","title":"Counterfactual Activation Editing for Post-hoc Prosody and Mispronunciation Correction in TTS Models","created":"2025-06-01","cited_by_count":3,"area":null},{"id":"2509.21293","title":"Optimal Robust Recourse with $L^p$-Bounded Model Change","created":"2025-09-25","cited_by_count":3,"area":null},{"id":"2205.07774","title":"Gradient-based Counterfactual Explanations using Tractable Probabilistic Models","created":"2022-05-16","cited_by_count":2,"area":null},{"id":"2306.05082","title":"The Importance of Time in Causal Algorithmic Recourse","created":"2023-06-08","cited_by_count":2,"area":null},{"id":"2403.10330","title":"Towards Non-Adversarial Algorithmic Recourse","created":"2024-03-15","cited_by_count":2,"area":null},{"id":"2409.13940","title":"Learning Recourse Costs from Pairwise Feature Comparisons","created":"2024-09-20","cited_by_count":2,"area":null},{"id":"2410.02273","title":"Perfect Counterfactuals in Imperfect Worlds: Modelling Noisy Implementation of Actions in Sequential Algorithmic Recourse","created":"2024-10-03","cited_by_count":2,"area":null},{"id":"2410.14640","title":"HR-Bandit: Human-AI Collaborated Linear Recourse Bandit","created":"2024-10-18","cited_by_count":2,"area":null},{"id":"2502.17613","title":"Flexible Counterfactual Explanations with Generative Models","created":"2025-02-24","cited_by_count":2,"area":null},{"id":"2505.23700","title":"DiCoFlex: Model-agnostic diverse counterfactuals with flexible control","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2601.18678","title":"Counterfactual Explanations on Robust Perceptual Geodesics","created":"2026-01-26","cited_by_count":2,"area":null},{"id":"2602.07674","title":"ElliCE: Efficient and Provably Robust Algorithmic Recourse via the Rashomon Sets","created":"2026-02-07","cited_by_count":2,"area":null},{"id":"2101.04230","title":"Explaining the Black-box Smoothly- A Counterfactual Approach","created":"2021-01-11","cited_by_count":1,"area":null},{"id":"2109.07869","title":"Explainability Requires Interactivity","created":"2021-09-16","cited_by_count":1,"area":null},{"id":"2211.06525","title":"Actionable Recourse via GANs for Mobile Health","created":"2022-11-12","cited_by_count":1,"area":null},{"id":"2305.06297","title":"Why Don't You Do Something About It? Outlining Connections between AI Explanations and User Actions","created":"2023-05-10","cited_by_count":1,"area":null},{"id":"2308.01614","title":"Assessing Systematic Weaknesses of DNNs using Counterfactuals","created":"2023-08-03","cited_by_count":1,"area":null},{"id":"2308.12367","title":"SafeAR: Safe Algorithmic Recourse by Risk-Aware Policies","created":"2023-08-23","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":"2404.03348","title":"Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual Explanations","created":"2024-04-04","cited_by_count":1,"area":null},{"id":"2404.17034","title":"Learning Actionable Counterfactual Explanations in Large State Spaces","created":"2024-04-25","cited_by_count":1,"area":null},{"id":"2410.20890","title":"Generative Example-Based Explanations: Bridging the Gap between Generative Modeling and Explainability","created":"2024-10-28","cited_by_count":1,"area":null},{"id":"2604.08030","title":"From Universal to Individualized Actionability: Revisiting Personalization in Algorithmic Recourse","created":"2026-04-09","cited_by_count":1,"area":null},{"id":"2605.06561","title":"Optimal Counterfactual Search in Tree Ensembles: A Study Across Modeling and Solution Paradigms","created":"2026-05-07","cited_by_count":1,"area":null},{"id":"2108.09159","title":"VAE-CE: Visual Contrastive Explanation using Disentangled VAEs","created":"2021-08-20","cited_by_count":0,"area":null},{"id":"2210.08902","title":"Beyond Model Interpretability: On the Faithfulness and Adversarial Robustness of Contrastive Textual Explanations","created":"2022-10-17","cited_by_count":0,"area":null},{"id":"2211.02151","title":"Decomposing Counterfactual Explanations for Consequential Decision Making","created":"2022-11-03","cited_by_count":0,"area":null},{"id":"2211.15370","title":"Clarity: an improved gradient method for producing quality visual counterfactual explanations","created":"2022-11-22","cited_by_count":0,"area":null},{"id":"2212.05256","title":"Causality-Aware Local Interpretable Model-Agnostic Explanations","created":"2022-12-10","cited_by_count":0,"area":null},{"id":"2301.07941","title":"CEnt: An Entropy-based Model-agnostic Explainability Framework to Contrast Classifiers' Decisions","created":"2023-01-19","cited_by_count":0,"area":null},{"id":"2302.05196","title":"Two-step counterfactual generation for OOD examples","created":"2023-02-10","cited_by_count":0,"area":null}],"next_cursor":"100"}