{"total":37,"rows":[{"id":"2202.01602","title":"The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective","created":"2022-02-03","cited_by_count":159,"area":null},{"id":"2206.11104","title":"OpenXAI: Towards a Transparent Evaluation of Model Explanations","created":"2022-06-22","cited_by_count":126,"area":null},{"id":"2103.04244","title":"Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications","created":"2021-03-07","cited_by_count":59,"area":null},{"id":"2205.14120","title":"Neural Basis Models for Interpretability","created":"2022-05-27","cited_by_count":56,"area":null},{"id":"2202.01875","title":"Rethinking Explainability as a Dialogue: A Practitioner's Perspective","created":"2022-02-03","cited_by_count":52,"area":null},{"id":"2211.00541","title":"Logic-Based Explainability in Machine Learning","created":"2022-10-24","cited_by_count":48,"area":null},{"id":"2102.10618","title":"Towards the Unification and Robustness of Perturbation and Gradient Based Explanations","created":"2021-02-21","cited_by_count":47,"area":null},{"id":"2205.07277","title":"Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations","created":"2022-05-15","cited_by_count":40,"area":null},{"id":"2111.01576","title":"Provably efficient, succinct, and precise explanations","created":"2021-11-01","cited_by_count":32,"area":null},{"id":"2107.08264","title":"M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis","created":"2021-07-17","cited_by_count":29,"area":null},{"id":"2109.00520","title":"The Role of Explainability in Assuring Safety of Machine Learning in Healthcare","created":"2021-09-01","cited_by_count":26,"area":null},{"id":"2302.12232","title":"Concept Learning for Interpretable Multi-Agent Reinforcement Learning","created":"2023-02-23","cited_by_count":19,"area":null},{"id":"2309.10058","title":"Dual Student Networks for Data-Free Model Stealing","created":"2023-09-18","cited_by_count":17,"area":null},{"id":"2403.09053","title":"Towards a theory of model distillation","created":"2024-03-14","cited_by_count":15,"area":null},{"id":"2206.02868","title":"A Human-Centric Take on Model Monitoring","created":"2022-06-06","cited_by_count":9,"area":null},{"id":"2210.06375","title":"Superpolynomial Lower Bounds for Decision Tree Learning and Testing","created":"2022-10-12","cited_by_count":9,"area":null},{"id":"2207.07072","title":"A Query-Optimal Algorithm for Finding Counterfactuals","created":"2022-07-14","cited_by_count":7,"area":null},{"id":"2406.10529","title":"A Theory of Interpretable Approximations","created":"2024-06-15","cited_by_count":7,"area":null},{"id":"2502.10556","title":"Recent Advances in Malware Detection: Graph Learning and Explainability","created":"2025-02-14","cited_by_count":7,"area":null},{"id":"2112.04934","title":"Model Doctor: A Simple Gradient Aggregation Strategy for Diagnosing and Treating CNN Classifiers","created":"2021-12-09","cited_by_count":6,"area":null},{"id":"2210.17426","title":"Trade-off Between Efficiency and Consistency for Removal-based Explanations","created":"2022-10-31","cited_by_count":6,"area":null},{"id":"2304.08275","title":"Implementing Responsible AI: Tensions and Trade-Offs Between Ethics Aspects","created":"2023-04-17","cited_by_count":6,"area":null},{"id":"2307.04093","title":"Properly Learning Decision Trees with Queries Is NP-Hard","created":"2023-07-09","cited_by_count":5,"area":null},{"id":"2504.05625","title":"Model-Agnostic Policy Explanations with Large Language Models","created":"2025-04-08","cited_by_count":4,"area":null},{"id":"2308.13755","title":"i-Align: an interpretable knowledge graph alignment model","created":"2023-08-26","cited_by_count":2,"area":null},{"id":"2605.12952","title":"Debunking Grad-ECLIP: A Comprehensive Study on Its Incorrectness and Fundamental Principles for Model Interpretation","created":"2026-05-13","cited_by_count":2,"area":null},{"id":"2103.06797","title":"BODAME: Bilevel Optimization for Defense Against Model Extraction","created":"2021-03-11","cited_by_count":1,"area":null},{"id":"2211.07719","title":"(When) Are Contrastive Explanations of Reinforcement Learning Helpful?","created":"2022-11-14","cited_by_count":1,"area":null},{"id":"2306.06473","title":"Interpretable Differencing of Machine Learning Models","created":"2023-06-10","cited_by_count":1,"area":null},{"id":"2311.01609","title":"Responsible Emergent Multi-Agent Behavior","created":"2023-11-02","cited_by_count":1,"area":null},{"id":"2408.15121","title":"Aligning XAI with EU Regulations for Smart Biomedical Devices: A Methodology for Compliance Analysis","created":"2024-08-27","cited_by_count":1,"area":null},{"id":"2502.19502","title":"Models That Are Interpretable But Not Transparent","created":"2025-02-26","cited_by_count":1,"area":null},{"id":"2503.09658","title":"Understanding Endogenous Data Drift in Adaptive Models with Recourse-Seeking Users","created":"2025-03-12","cited_by_count":1,"area":null},{"id":"2505.07005","title":"Explainable AI the Latest Advancements and New Trends","created":"2025-05-11","cited_by_count":1,"area":null},{"id":"2112.12717","title":"Forward Composition Propagation for Explainable Neural Reasoning","created":"2021-12-23","cited_by_count":0,"area":null},{"id":"2304.04354","title":"ViT-Calibrator: Decision Stream Calibration for Vision Transformer","created":"2023-04-10","cited_by_count":0,"area":null},{"id":"2604.09799","title":"Explainable Human Activity Recognition: A Unified Review of Concepts and Mechanisms","created":"2026-04-10","cited_by_count":0,"area":null}],"next_cursor":null}