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Low-confidence training samples are secretly sabotaging your fast adversarial training, leading to catastrophic overfitting and a worse robustness-accuracy trade-off.
Catastrophic overfitting in fast adversarial training isn't just overfitting – it's a backdoor, and now we can use backdoor defenses to fix it.
