Adversarial distillation improves student robustness when teachers show high uncertainty on robustly unlearnable samples, suppressing noise memorization and allowing reliance on learnable robust signals.
(439) The learnable contribution is bounded as in Theorem G.2, and the unlearnable contribution is bounded by conditions (C2), (C7) and (C8)
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Toward Understanding Adversarial Distillation: Why Robust Teachers Fail
Adversarial distillation improves student robustness when teachers show high uncertainty on robustly unlearnable samples, suppressing noise memorization and allowing reliance on learnable robust signals.