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cs.CV2024
CLIP-Guided Generative Networks for Transferable Targeted Adversarial Attacks
Hao Fang, Jiawei Kong, Bin Chen +3
Transferable targeted adversarial attacks aim to mislead models into outputting adversary-specified predictions in black-box scenarios. Recent studies have introduced \textit{singl…
cs.CV2024
One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models
Hao Fang, Jiawei Kong, Wenbo Yu +5
Vision-Language Pre-training (VLP) models have exhibited unprecedented capability in many applications by taking full advantage of the multimodal alignment. However, previous studi…