8 papers
MarkNull: Model-Agnostic Watermark Removal in AI-Generated Images via On-Manifold Latent Manipulation
Jie Cao, Qi Li, Zelin Zhang +4
Digital watermarking has emerged as a critical technique for provenance and copyright attribution in AI-generated imagery, yet its robustness against realistic, model-agnostic remo…
SoK: A Comprehensive Security Analysis of Jailbreak Resilience in GPT and DeepSeek Models
Xiaodong Wu, Xiangman Li, Qi Li +2
The rapid proliferation of Large Language Models (LLMs) has heightened concerns regarding their exposure to jailbreak attacks, which craft adversarial inputs designed to elicit uns…
Are Watermarked Images Editable? SafeMark for Watermark-Preserving Text-Guided Image Editing
Xiaodong Wu, Qi Li, Xiangman Li +3
This paper investigates a fundamental yet underexplored question: can watermarked images remain editable without compromising watermark integrity? We propose SafeMark, a framework…
SafeLLM: Unlearning Harmful Outputs from Large Language Models against Jailbreak Attacks
Xiangman Li, Xiaodong Wu, Qi Li +2
Jailbreak attacks pose a serious threat to the safety of Large Language Models (LLMs) by crafting adversarial prompts that bypass alignment mechanisms, causing the models to produc…
When There Is No Decoder: Removing Watermarks from Stable Diffusion Models in a No-box Setting
Xiaodong Wu, Tianyi Tang, Xiangman Li +2
Watermarking has emerged as a promising solution to counter harmful or deceptive AI-generated content by embedding hidden identifiers that trace content origins. However, the robus…
SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts
Xiaodong Wu, Xiangman Li, Qi Li +2
Text-guided image manipulation with diffusion models enables flexible and precise editing based on prompts, but raises ethical and copyright concerns due to potential unauthorized…