{"total":25,"rows":[{"id":"2202.00449","title":"A Consistent and Efficient Evaluation Strategy for Attribution Methods","created":"2022-02-01","cited_by_count":102,"area":null},{"id":"2309.12325","title":"FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare","created":"2023-08-11","cited_by_count":60,"area":null},{"id":"2211.04533","title":"Harmonizing the object recognition strategies of deep neural networks with humans","created":"2022-11-08","cited_by_count":59,"area":null},{"id":"2202.00734","title":"Framework for Evaluating Faithfulness of Local Explanations","created":"2022-02-01","cited_by_count":55,"area":null},{"id":"2210.07394","title":"Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation","created":"2022-10-13","cited_by_count":45,"area":null},{"id":"2110.14297","title":"Revisiting Sanity Checks for Saliency Maps","created":"2021-10-27","cited_by_count":20,"area":null},{"id":"2110.13369","title":"Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set","created":"2021-10-26","cited_by_count":12,"area":null},{"id":"2206.06854","title":"On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective","created":"2022-06-14","cited_by_count":6,"area":null},{"id":"2206.12481","title":"Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions","created":"2022-06-24","cited_by_count":6,"area":null},{"id":"2211.04780","title":"On the Robustness of Explanations of Deep Neural Network Models: A Survey","created":"2022-11-09","cited_by_count":5,"area":null},{"id":"2407.19683","title":"Revisiting the robustness of post-hoc interpretability methods","created":"2024-07-29","cited_by_count":5,"area":null},{"id":"2203.07861","title":"Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series","created":"2022-03-14","cited_by_count":4,"area":null},{"id":"2306.06716","title":"On Minimizing the Impact of Dataset Shifts on Actionable Explanations","created":"2023-06-11","cited_by_count":3,"area":null},{"id":"2307.09591","title":"Saliency strikes back: How filtering out high frequencies improves white-box explanations","created":"2023-07-18","cited_by_count":3,"area":null},{"id":"2309.10989","title":"COSE: A Consistency-Sensitivity Metric for Saliency on Image Classification","created":"2023-09-20","cited_by_count":2,"area":null},{"id":"2411.01126","title":"Axiomatic Explainer Globalness via Optimal Transport","created":"2024-11-02","cited_by_count":2,"area":null},{"id":"2507.11099","title":"A Survey on Interpretability in Visual Recognition","created":"2025-07-15","cited_by_count":2,"area":null},{"id":"2302.12094","title":"Evaluating Explainability in Machine Learning Predictions through Explainer-Agnostic Metrics","created":"2023-02-23","cited_by_count":1,"area":null},{"id":"2411.05837","title":"Gaussian Smoothing in Saliency Maps: The Stability-Fidelity Trade-Off in Neural Network Interpretability","created":"2024-11-06","cited_by_count":1,"area":null},{"id":"2305.02368","title":"Metric Tools for Sensitivity Analysis with Applications to Neural Networks","created":"2023-05-03","cited_by_count":0,"area":null},{"id":"2306.12495","title":"Verifying Global Neural Network Specifications using Hyperproperties","created":"2023-06-21","cited_by_count":0,"area":null},{"id":"2512.06665","title":"Rethinking Robustness: A New Approach to Evaluating Feature Attribution Methods","created":"2025-12-07","cited_by_count":0,"area":null},{"id":"2512.21208","title":"A Learning Stability Profile for Finite-Dimensional Learning Dynamics","created":"2025-12-24","cited_by_count":0,"area":null},{"id":"2603.22624","title":"Toward Faithful Segmentation Attribution via Benchmarking and Dual-Evidence Fusion","created":"2026-03-23","cited_by_count":0,"area":null},{"id":"2604.04456","title":"Empirical Characterization of Rationale Stability Under Controlled Perturbations for Explainable Pattern Recognition","created":"2026-04-06","cited_by_count":0,"area":null}],"next_cursor":null}