Concept-level adversarial attacks exploit CBM interpretability on the CUB dataset, but SPECTRA raises required perturbation norm from 0.46 to over 4200 while keeping accuracy loss under 2.2%.
A closer look at the adversarial robustness of information bottleneck models.arXiv preprint arXiv:2107.05712, 2021
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When Interpretability Becomes a Liability: Adversarial Attacks on CBM Concept Layers
Concept-level adversarial attacks exploit CBM interpretability on the CUB dataset, but SPECTRA raises required perturbation norm from 0.46 to over 4200 while keeping accuracy loss under 2.2%.