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Mar, 2024
视觉-语言模型上的少样本对抗性提示学习
Few-Shot Adversarial Prompt Learning on Vision-Language Models
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Yiwei Zhou, Xiaobo Xia, Zhiwei Lin, Bo Han, Tongliang Liu
TL;DR
通过限制数据和提供对抗文本监督,提出了一种少样本对抗提示框架,该框架在提高对抗鲁棒性方面表现出卓越的能力,并在仅使用1%的训练数据时,达到了与最先进的零样本对抗鲁棒性相匹配的水平。
Abstract
The vulnerability of
deep neural networks
to imperceptible
adversarial perturbations
has attracted widespread attention. Inspired by the success of vision-language foundation models, previous efforts achieved zer
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