Related Issues (20)
- OpenXAI: Towards a Transparent Evaluation of Model Explanations HOT 1
- Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations
- Preventing deception with explanation methods using focused sampling HOT 1
- On the robustness of sparse counterfactual explanations to adverse perturbations
- Disguising Attacks with Explanation-Aware Backdoors
- Certifiably robust interpretation via Rényi differential privacy
- Resilience of Bayesian Layer-Wise Explanations under Adversarial Attacks
- Adversarial Inter-Group Link Injection Degrades the Fairness of Graph Neural Networks
- Exploiting Fairness to Enhance Sensitive Attributes Reconstruction
- Don't trust your eyes: on the (un)reliability of feature visualizations
- "Is your explanation stable?": A Robustness Evaluation Framework for Feature Attribution
- SAFARI: Versatile and Efficient Evaluations for Robustness of Interpretability
- On Minimizing the Impact of Dataset Shifts on Actionable Explanations
- On the Robustness of Removal-Based Feature Attributions
- Focus-Shifting Attack: An Adversarial Attack That Retains Saliency Map Information and Manipulates Model Explanations
- Foiling Explanations in Deep Neural Networks
- Interpretation Attacks and Defenses on Predictive Models Using Electronic Health Records
- SoK: Explainable Machine Learning in Adversarial Environments
- Unfooling SHAP and SAGE: Knockoff Imputation for Shapley Values
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