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- license: apache-2.0
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+ license: apache-2.0
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+ pipeline_tag: zero-shot-image-classification
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+ ---
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+ # Towards Highly Transferable Vision-Language Attack via Semantic-Augmented Dynamic Contrastive Interaction
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+ This repository contains the official implementation of **SADCA** (Semantic-Augmented Dynamic Contrastive Attack), presented in the paper [Towards Highly Transferable Vision-Language Attack via Semantic-Augmented Dynamic Contrastive Interaction](https://arxiv.org/abs/2603.04839).
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+ SADCA is a framework designed to enhance the transferability of adversarial attacks against vision-language pre-training (VLP) models. It progressively disrupts cross-modal alignment through dynamic interactions between adversarial images and texts, using a contrastive learning mechanism involving adversarial, positive, and negative samples to reinforce semantic inconsistency.
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+ ## Links
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+ - **Paper**: [https://arxiv.org/abs/2603.04839](https://arxiv.org/abs/2603.04839)
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+ - **GitHub**: [https://github.com/LiYuanBoJNU/SADCA](https://github.com/LiYuanBoJNU/SADCA)
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+
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+ ## Citation
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+ ```bibtex
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+ @article{li2026towards,
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+ title={Towards Highly Transferable Vision-Language Attack via Semantic-Augmented Dynamic Contrastive Interaction},
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+ author={Li, Yuanbo and Xu, Tianyang and Hu, Cong and Zhou, Tao and Wu, Xiao-Jun and Kittler, Josef},
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+ journal={arXiv preprint arXiv:2603.04839},
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+ year={2026}
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+ }
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+ ```