{"total":28,"rows":[{"id":"2209.11222","title":"Concept Activation Regions: A Generalized Framework For Concept-Based Explanations","created":"2022-09-22","cited_by_count":57,"area":null},{"id":"2208.00780","title":"Visual correspondence-based explanations improve AI robustness and human-AI team accuracy","created":"2022-07-26","cited_by_count":39,"area":null},{"id":"2303.05506","title":"TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization","created":"2023-03-09","cited_by_count":32,"area":null},{"id":"2403.00025","title":"On the Challenges and Opportunities in Generative AI","created":"2024-02-28","cited_by_count":31,"area":null},{"id":"2206.08363","title":"Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability","created":"2022-06-16","cited_by_count":15,"area":null},{"id":"2203.01928","title":"Label-Free Explainability for Unsupervised Models","created":"2022-03-03","cited_by_count":14,"area":null},{"id":"2304.06715","title":"Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance","created":"2023-04-13","cited_by_count":14,"area":null},{"id":"2503.23616","title":"Interpretable Machine Learning in Physics: A Review","created":"2025-03-30","cited_by_count":14,"area":null},{"id":"2212.02648","title":"Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases","created":"2022-12-05","cited_by_count":13,"area":null},{"id":"2210.12090","title":"AutoPrognosis 2.0: Democratizing Diagnostic and Prognostic Modeling in Healthcare with Automated Machine Learning","created":"2022-10-21","cited_by_count":10,"area":null},{"id":"2303.09234","title":"NAISR: A 3D Neural Additive Model for Interpretable Shape Representation","created":"2023-03-16","cited_by_count":7,"area":null},{"id":"2207.05161","title":"What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization","created":"2022-07-11","cited_by_count":5,"area":null},{"id":"2309.04211","title":"Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse","created":"2023-09-08","cited_by_count":3,"area":null},{"id":"2407.18227","title":"Automated Ensemble Multimodal Machine Learning for Healthcare","created":"2024-07-25","cited_by_count":3,"area":null},{"id":"2311.03246","title":"Advancing Post Hoc Case Based Explanation with Feature Highlighting","created":"2023-11-06","cited_by_count":2,"area":null},{"id":"2311.17560","title":"Interpreting Differentiable Latent States for Healthcare Time-series Data","created":"2023-11-29","cited_by_count":2,"area":null},{"id":"2412.08515","title":"Enhancing Interpretability Through Loss-Defined Classification Objective in Structured Latent Spaces","created":"2024-12-11","cited_by_count":2,"area":null},{"id":"2311.07426","title":"Optimising Human-AI Collaboration by Learning Convincing Explanations","created":"2023-11-13","cited_by_count":1,"area":null},{"id":"2405.10552","title":"Data Science Principles for Interpretable and Explainable AI","created":"2024-05-17","cited_by_count":1,"area":null},{"id":"2504.03847","title":"Interpretable Multimodal Learning for Tumor Protein-Metal Binding: Progress, Challenges, and Perspectives","created":"2025-04-04","cited_by_count":1,"area":null},{"id":"2504.20667","title":"Explanations Go Linear: Post-hoc Explainability for Tabular Data with Interpretable Meta-Encoding","created":"2025-04-29","cited_by_count":1,"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":"2402.04068","title":"Retrieve to Explain: Evidence-driven Predictions for Explainable Drug Target Identification","created":"2024-02-06","cited_by_count":0,"area":null},{"id":"2406.17885","title":"Enabling Regional Explainability by Automatic and Model-agnostic Rule Extraction","created":"2024-06-25","cited_by_count":0,"area":null},{"id":"2411.00139","title":"Learning local discrete features in explainable-by-design convolutional neural networks","created":"2024-10-31","cited_by_count":0,"area":null},{"id":"2502.08445","title":"LucidAtlas: Learning Uncertainty-Aware, Covariate-Disentangled, Individualized Atlas Representations","created":"2025-02-12","cited_by_count":0,"area":null},{"id":"2601.13899","title":"Towards Visually Explaining Statistical Tests with Applications in Biomedical Imaging","created":"2026-01-20","cited_by_count":0,"area":null},{"id":"2602.10239","title":"XSPLAIN: XAI-enabling Splat-based Prototype Learning for Attribute-aware INterpretability","created":"2026-02-10","cited_by_count":0,"area":null}],"next_cursor":null}