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SotA/Adversarial/Adversarial Defense/CIFAR-10

Adversarial Defense on CIFAR-10

Metric: Accuracy (higher is better)

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#Model↕Accuracy▼Extra DataPaperDate↕Code
1WRN-28-1090.03YesLanguage Guided Adversarial Purification2023-09-19Code
2Diffusion Classifier89.85NoRobust Classification via a Single Diffusion Model2023-05-24Code
3Stochastic-LWTA/PGD/WideResNet-34-1084.3NoStochastic Local Winner-Takes-All Networks Enabl...2021-12-05Code
4Ours (Stochastic-LWTA/PGD/WideResNet-34-5)83.4NoStochastic Local Winner-Takes-All Networks Enabl...2021-12-05Code
5Ours (Stochastic-LWTA/PGD/WideResNet-34-1)81.87NoStochastic Local Winner-Takes-All Networks Enabl...2021-12-05Code
6ResNet18 (TRADES-ANCRA/PGD-40)81.7NoEnhancing Robust Representation in Adversarial T...2023-10-05Code
7SLL X-Large70.3NoA Unified Algebraic Perspective on Lipschitz Neu...2023-03-06Code
8SLL Large69.8NoA Unified Algebraic Perspective on Lipschitz Neu...2023-03-06Code
9SLL Medium69.1NoA Unified Algebraic Perspective on Lipschitz Neu...2023-03-06Code
10SLL Small68.1NoA Unified Algebraic Perspective on Lipschitz Neu...2023-03-06Code
11PCL (against PGD, white box)46.7NoAdversarial Defense by Restricting the Hidden Sp...2019-04-01Code