AI RESEARCH
Complementary Text-Guided Attention for Zero-Shot Adversarial Robustness
arXiv CS.CV
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ArXi:2603.18598v1 Announce Type: new Due to the impressive zero-shot capabilities, pre-trained vision-language models (e.g., CLIP), have attracted widespread attention and adoption across various domains. Nonetheless, CLIP has been observed to be susceptible to adversarial examples. Through experimental analysis, we have observed a phenomenon wherein adversarial perturbations induce shifts in text-guided attention. Building upon this observation, we propose a simple yet effective strategy: Text-Guided Attention for Zero-Shot Robustness.