AINeutralarXiv – CS AI · Mar 126/10
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Contract And Conquer: How to Provably Compute Adversarial Examples for a Black-Box Model?
Researchers propose Contract And Conquer (CAC), a new method for provably generating adversarial examples against black-box neural networks using knowledge distillation and search space contraction. The approach provides theoretical guarantees for finding adversarial examples within a fixed number of iterations and outperforms existing methods on ImageNet datasets including vision transformers.