{"total":89,"rows":[{"id":"2310.19775","title":"Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions","created":"2023-10-30","cited_by_count":125,"area":null},{"id":"2209.04012","title":"From Shapley Values to Generalized Additive Models and back","created":"2022-09-08","cited_by_count":60,"area":null},{"id":"2106.12543","title":"Synthetic Benchmarks for Scientific Research in Explainable Machine Learning","created":"2021-06-23","cited_by_count":59,"area":null},{"id":"2201.10295","title":"Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts","created":"2022-01-25","cited_by_count":53,"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":"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":"2106.06054","title":"Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline","created":"2021-06-02","cited_by_count":49,"area":null},{"id":"2106.09078","title":"Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods","created":"2021-06-16","cited_by_count":36,"area":null},{"id":"2102.06307","title":"What does LIME really see in images?","created":"2021-02-11","cited_by_count":21,"area":null},{"id":"2309.14531","title":"Pixel-Grounded Prototypical Part Networks","created":"2023-09-25","cited_by_count":18,"area":null},{"id":"2102.07048","title":"Connecting Interpretability and Robustness in Decision Trees through Separation","created":"2021-02-14","cited_by_count":16,"area":null},{"id":"2106.15566","title":"Near-Optimal Explainable $k$-Means for All Dimensions","created":"2021-06-29","cited_by_count":13,"area":null},{"id":"2205.14772","title":"Unfooling Perturbation-Based Post Hoc Explainers","created":"2022-05-29","cited_by_count":12,"area":null},{"id":"2306.01464","title":"Theoretical Behavior of XAI Methods in the Presence of Suppressor Variables","created":"2023-06-02","cited_by_count":12,"area":null},{"id":"2305.12351","title":"Are Your Explanations Reliable? Investigating the Stability of LIME in Explaining Text Classifiers by Marrying XAI and Adversarial Attack","created":"2023-05-21","cited_by_count":10,"area":null},{"id":"2103.03302","title":"Ensembles of Random SHAPs","created":"2021-03-04","cited_by_count":8,"area":null},{"id":"2208.01510","title":"s-LIME: Reconciling Locality and Fidelity in Linear Explanations","created":"2022-08-02","cited_by_count":8,"area":null},{"id":"2402.02870","title":"Rethinking Explainable Machine Learning as Applied Statistics","created":"2024-02-05","cited_by_count":8,"area":null},{"id":"2405.13536","title":"Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for Transformers","created":"2024-05-22","cited_by_count":8,"area":null},{"id":"2209.03415","title":"A Survey of Neural Trees","created":"2022-09-07","cited_by_count":7,"area":null},{"id":"2306.13885","title":"Manipulation Risks in Explainable AI: The Implications of the Disagreement Problem","created":"2023-06-24","cited_by_count":7,"area":null},{"id":"2312.00586","title":"Explainable Fraud Detection with Deep Symbolic Classification","created":"2023-12-01","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":"2106.07221","title":"Certification of embedded systems based on Machine Learning: A survey","created":"2021-06-14","cited_by_count":6,"area":null},{"id":"2106.09111","title":"An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data","created":"2021-06-16","cited_by_count":6,"area":null},{"id":"2108.02662","title":"Reducing Unintended Bias of ML Models on Tabular and Textual Data","created":"2021-08-05","cited_by_count":6,"area":null},{"id":"2111.09121","title":"Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach","created":"2021-11-17","cited_by_count":6,"area":null},{"id":"2205.13789","title":"A Sea of Words: An In-Depth Analysis of Anchors for Text Data","created":"2022-05-27","cited_by_count":6,"area":null},{"id":"2210.11318","title":"A Survey of Computer Vision Technologies In Urban and Controlled-environment Agriculture","created":"2022-10-20","cited_by_count":6,"area":null},{"id":"2308.04708","title":"Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution","created":"2023-08-09","cited_by_count":6,"area":null},{"id":"2405.13474","title":"Why do explanations fail? A typology and discussion on failures in XAI","created":"2024-05-22","cited_by_count":6,"area":null},{"id":"2208.04638","title":"A Means-End Account of Explainable Artificial Intelligence","created":"2022-08-09","cited_by_count":5,"area":null},{"id":"2509.03626","title":"Explainable Knowledge Graph Retrieval-Augmented Generation (KG-RAG) with KG-SMILE","created":"2025-09-03","cited_by_count":4,"area":"rag"},{"id":"2106.08376","title":"A Framework for Evaluating Post Hoc Feature-Additive Explainers","created":"2021-06-15","cited_by_count":3,"area":null},{"id":"2108.04855","title":"Attention-like feature explanation for tabular data","created":"2021-08-10","cited_by_count":3,"area":null},{"id":"2205.09620","title":"Towards a Theory of Faithfulness: Faithful Explanations of Differentiable Classifiers over Continuous Data","created":"2022-05-19","cited_by_count":3,"area":null},{"id":"2308.03730","title":"SurvBeX: An explanation method of the machine learning survival models based on the Beran estimator","created":"2023-08-07","cited_by_count":3,"area":null},{"id":"2403.17742","title":"Using Stratified Sampling to Improve LIME Image Explanations","created":"2024-03-26","cited_by_count":3,"area":null},{"id":"2404.11428","title":"Explainable Lung Disease Classification from Chest X-Ray Images Utilizing Deep Learning and XAI","created":"2024-04-17","cited_by_count":3,"area":null},{"id":"2410.17269","title":"FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction","created":"2024-10-07","cited_by_count":3,"area":null},{"id":"2410.19361","title":"Engineering Trustworthy AI: A Developer Guide for Empirical Risk Minimization","created":"2024-10-25","cited_by_count":3,"area":null},{"id":"2412.16277","title":"Mapping the Mind of an Instruction-based Image Editing using SMILE","created":"2024-12-20","cited_by_count":3,"area":null},{"id":"2504.12151","title":"Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis","created":"2025-04-16","cited_by_count":3,"area":null},{"id":"2504.16148","title":"Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room","created":"2025-04-22","cited_by_count":3,"area":null},{"id":"2111.08749","title":"SMACE: A New Method for the Interpretability of Composite Decision Systems","created":"2021-11-16","cited_by_count":2,"area":null},{"id":"2310.18496","title":"How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors?","created":"2023-10-27","cited_by_count":2,"area":null},{"id":"2311.01605","title":"Faithful and Robust Local Interpretability for Textual Predictions","created":"2023-10-30","cited_by_count":2,"area":null},{"id":"2502.03773","title":"ExpProof : Operationalizing Explanations for Confidential Models with ZKPs","created":"2025-02-06","cited_by_count":2,"area":null},{"id":"2505.08064","title":"Justified Evidence Collection for Argument-based AI Fairness Assurance","created":"2025-05-12","cited_by_count":2,"area":null},{"id":"2508.07636","title":"Attribution Explanations for Deep Neural Networks: A Theoretical Perspective","created":"2025-08-11","cited_by_count":2,"area":null},{"id":"2508.11441","title":"Informative Post-Hoc Explanations Only Exist for Simple Functions","created":"2025-08-15","cited_by_count":2,"area":null},{"id":"2601.02224","title":"From XAI to Stories: A Factorial Study of LLM-Generated Explanation Quality","created":"2026-01-05","cited_by_count":2,"area":"lr"},{"id":"2602.02560","title":"Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional Attributions","created":"2026-01-30","cited_by_count":2,"area":null},{"id":"2107.09927","title":"GLIME: A new graphical methodology for interpretable model-agnostic explanations","created":"2021-07-21","cited_by_count":1,"area":null},{"id":"2201.09286","title":"How to scale hyperparameters for quickshift image segmentation","created":"2022-01-23","cited_by_count":1,"area":null},{"id":"2301.12891","title":"Half of an image is enough for quality assessment","created":"2023-01-30","cited_by_count":1,"area":null},{"id":"2302.07733","title":"Explaining text classifiers through progressive neighborhood approximation with realistic samples","created":"2023-02-11","cited_by_count":1,"area":null},{"id":"2303.08806","title":"Understanding Post-hoc Explainers: The Case of Anchors","created":"2023-03-15","cited_by_count":1,"area":null},{"id":"2312.06255","title":"Ensemble Interpretation: A Unified Method for Interpretable Machine Learning","created":"2023-12-11","cited_by_count":1,"area":null},{"id":"2402.11664","title":"Interpretable Short-Term Load Forecasting via Multi-Scale Temporal Decomposition","created":"2024-02-18","cited_by_count":1,"area":null},{"id":"2404.01078","title":"Energy-Based Model for Accurate Estimation of Shapley Values in Feature Attribution","created":"2024-04-01","cited_by_count":1,"area":null},{"id":"2406.15839","title":"The Effect of Similarity Measures on Accurate Stability Estimates for Local Surrogate Models in Text-based Explainable AI","created":"2024-06-22","cited_by_count":1,"area":null},{"id":"2407.07521","title":"CHILLI: A data context-aware perturbation method for XAI","created":"2024-07-10","cited_by_count":1,"area":null},{"id":"2501.02042","title":"Towards Robust and Accurate Stability Estimation of Local Surrogate Models in Text-based Explainable AI","created":"2025-01-03","cited_by_count":1,"area":null},{"id":"2506.22740","title":"Explanations are a Means to an End: Decision Theoretic Explanation Evaluation","created":"2025-06-28","cited_by_count":1,"area":null},{"id":"2604.11223","title":"Regional Explanations: Bridging Local and Global Variable Importance","created":"2026-04-13","cited_by_count":1,"area":null},{"id":"2202.01013","title":"Fairness of Machine Learning Algorithms in Demography","created":"2022-02-02","cited_by_count":0,"area":null},{"id":"2212.12374","title":"Relational Local Explanations","created":"2022-12-23","cited_by_count":0,"area":null},{"id":"2310.04856","title":"LIPEx-Locally Interpretable Probabilistic Explanations-To Look Beyond The True Class","created":"2023-10-07","cited_by_count":0,"area":null},{"id":"2311.12404","title":"InterPrompt: Interpretable Prompting for Interrelated Interpersonal Risk Factors in Reddit Posts","created":"2023-11-21","cited_by_count":0,"area":null},{"id":"2311.17446","title":"Uncertainty in Additive Feature Attribution methods","created":"2023-11-29","cited_by_count":0,"area":null},{"id":"2312.06638","title":"SurvBeNIM: The Beran-Based Neural Importance Model for Explaining the Survival Models","created":"2023-12-11","cited_by_count":0,"area":null},{"id":"2312.12715","title":"Learning Performance Maximizing Ensembles with Explainability Guarantees","created":"2023-12-20","cited_by_count":0,"area":null},{"id":"2401.16294","title":"Dual feature-based and example-based explanation methods","created":"2024-01-29","cited_by_count":0,"area":null},{"id":"2402.18600","title":"Artificial Intelligence and Diabetes Mellitus: An Inside Look Through the Retina","created":"2024-02-28","cited_by_count":0,"area":null},{"id":"2502.07741","title":"Advancing climate model interpretability: Feature attribution for Arctic melt anomalies","created":"2025-02-11","cited_by_count":0,"area":null},{"id":"2509.10506","title":"AttnBoost: Retail Supply Chain Sales Insights via Gradient Boosting Perspective","created":"2025-09-01","cited_by_count":0,"area":null},{"id":"2511.06607","title":"Explainable Probabilistic Machine Learning for Predicting Drilling Fluid Loss of Circulation in Marun Oil Field","created":"2025-11-10","cited_by_count":0,"area":null},{"id":"2512.11081","title":"Provable Recovery of Locally Important Signed Features and Interactions from Random Forest","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2603.06555","title":"Hierarchical Industrial Demand Forecasting with Temporal and Uncertainty Explanations","created":"2026-03-06","cited_by_count":0,"area":null},{"id":"2603.24323","title":"Connecting Meteorite Spectra to Lunar Surface Composition Using Hyperspectral Imaging and Machine Learning","created":"2026-03-25","cited_by_count":0,"area":null},{"id":"2604.16689","title":"The Query Channel: Information-Theoretic Limits of Masking-Based Explanations","created":"2026-04-17","cited_by_count":0,"area":null},{"id":"2604.26219","title":"eDySec: A Deep Learning-based Explainable Dynamic Analysis Framework for Detecting Malicious Packages in PyPI Ecosystem","created":"2026-04-29","cited_by_count":0,"area":null},{"id":"2605.15688","title":"$\\alpha$-TCAV: A Unified Framework for Testing with Concept Activation Vectors","created":"2026-05-15","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":"2606.27973","title":"From Black-Box to Clinical Insight: A Multi-Stage Explainable Framework for Speech-Based Cognitive Impairment Detection","created":"2026-06-26","cited_by_count":0,"area":null},{"id":"2607.17789","title":"Medical Imaging Fusing Vision Transformer: Laryngeal Cancer Screening with Explanation","created":"2026-07-20","cited_by_count":0,"area":null},{"id":"2608.23538","title":"Interpretable AI with Local Distillation","created":"2026-08-24","cited_by_count":0,"area":"distill"},{"id":"2609.19077","title":"Probabilistic Linear Explanations","created":"2026-09-16","cited_by_count":0,"area":null}],"next_cursor":null}