activity
20242026
collaborators

11 papers

cs.CR2026

SkillShield: Prompt-Space Security Skills for LLM Coding Agents

Xiaodong Wu, Zhimin Zhao, Qi Li +4

A coding agent edits files and executes shell commands with its developer's privileges, allowing malicious requests to translate directly into harmful actions or functional malware…

cs.CR2026

EVOMAL: Self-Poisoning in Self-Evolving Coding Agents

Xiaodong Wu, Yu Shi, Qi Li +5

Self-evolving LLM coding agents write their own tools by imitating retrieved skills from shared skill libraries. We identify a vulnerability in this loop: during authoring, a retri…

cs.CR2026

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…

cs.RO2026

HyperSim: A Holistic Sim-To-Real Framework For Robust Robotic Manipulation

Junyi Dong, Haotian Luo, Ziwei Xu +11

Scaling data volume and diversity is critical for generalizing embodied intelligence. While synthetic data generation offers a scalable alternative to expensive physical data acqui…

cs.CV2026

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…

cs.LG2025

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…

cs.CR2025

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…

cs.CR2025

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…

cs.CR2025

PDLRecover: Privacy-preserving Decentralized Model Recovery with Machine Unlearning

Xiangman Li, Xiaodong Wu, Jianbing Ni +2

Decentralized learning is vulnerable to poison attacks, where malicious clients manipulate local updates to degrade global model performance. Existing defenses mainly detect and fi…

cs.CR2025

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…

cs.CR2024

Robustness of Watermarking on Text-to-Image Diffusion Models

Xiaodong Wu, Xiangman Li, Jianbing Ni

Watermarking has become one of promising techniques to not only aid in identifying AI-generated images but also serve as a deterrent against the unethical use of these models. Howe…