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Found 2 papers, 2 papers with code
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
The CLIP model, or one of its variants, is used as a frozen vision encoder in many vision-language models (VLMs), e. g. LLaVA and OpenFlamingo.
On the Adversarial Robustness of Multi-Modal Foundation Models
In this paper we show that imperceivable attacks on images in order to change the caption output of a multi-modal foundation model can be used by malicious content providers to harm honest users e. g. by guiding them to malicious websites or broadcast fake information.
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