Unverified50% confidenceFactExact time
Adversarial examples exploit the fragility of the model's decision boundary in high-dimensional space; the network's robustness mechanisms (such as normalization and Dropout) are effective against random noise but almost ineffective against adversarial perturbations, because the perturbation direction is exactly the gradient ascent direction.
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10/15/2026
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