1 citations · 3 across the 12 of their papers we have counts for
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TYPO: Instruction-Dense Visual Jailbreaks against Commercial Closed-Source Image-Generation Models
Meng Xie, Li Zeng, Hangtao Zhang +4
Recent commercial image-generation models can generate high-quality images with readable text (e.g., posters, infographics, and manuals), attracting considerable attention. Yet we…
GhostPrompt: Cross-Image Adversarial Prompt for Vision-Language Models
Li Zeng, Zeyu Ye, Meng Xie +4
Vision-Language Models (VLMs) are known to be vulnerable to adversarial attacks, where subtle perturbations to images or texts induce erroneous outputs. However, most text-based at…
Dual-branch Robust Unlearnable Examples
Xianlong Wang, Hangtao Zhang, Wenbo Pan +4
Unlearnable examples (UEs) aim to compromise model training by injecting imperceptible perturbations to clean samples. However, existing UE schemes exhibit limited robustness again…
Image-to-Video Diffusion: From Foundations to Open Frontiers
Xianlong Wang, Wenbo Pan, Shijia Zhou +6
Diffusion-based \textit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional conditions, into a temporal…