ABE is a PyTorch framework that integrates attribution algorithms with adversarial robustness modules, but its central axiom-preservation proof rests on an unproven finite-step Taylor equality.
Evaluating the quality of machine learning explanations: A survey on methods and metrics,
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ABE: A Unified Framework for Robust and Faithful Attribution-Based Explainability
ABE is a PyTorch framework that integrates attribution algorithms with adversarial robustness modules, but its central axiom-preservation proof rests on an unproven finite-step Taylor equality.