TARO builds a temporally guided score prior from high-noise and low-noise diffusion views to purify adversarial examples more robustly than uniform timestep methods.
Adversarial robustness on in-and out-distribution improves explainability.arXiv preprint arXiv:2003.09461
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TARO: Temporal Adversarial Rectification Optimization Using Diffusion Models as Purifiers
TARO builds a temporally guided score prior from high-noise and low-noise diffusion views to purify adversarial examples more robustly than uniform timestep methods.