8 papers · 1 filter
When the Editing Intent Is Split: A Cross-Modal Jailbreak Attack for Large Image Editing Models
Xianmin Ye, Zhiyuan Fan, Tianju Liu +3
Large image editing models increasingly infer editing intent from both textual and visual inputs, creating an underexplored safety risk when harmful intent is distributed across mo…
A Model Merging Approach for Continual MLLM Unlearning
Yuhang Wang, Linlin Zhang, Haoxuan Ji +3
Multimodal large language model (MLLM) unlearning methods have been proposed to remove private, sensitive, or proprietary information from well-trained models. However, most existi…
PlanFlip: Attacking Multi-Agent LLM Systems via Planning-Phase Prompt Injection
Yuhang Wang
Multi-agent LLM systems increasingly rely on a Planner to decompose goals into sub-task sequences that downstream Executor and Critic agents execute and audit. We identify the plan…
Null Space Constrained Contrastive Visual Forgetting for MLLM Unlearning
Yuhang Wang, Zhenxing Niu, Haoxuan Ji +3
The core challenge of machine unlearning is to strike a balance between target knowledge removal and non-target knowledge retention. In the context of Multimodal Large Language Mod…
ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models
Yuhang Wang, Wenjie Mei, Junkai Zhang +3
Privacy deletion requests often arrive sequentially, creating a continual unlearning challenge for deployed multimodal large language models (MLLMs). However, existing benchmarks m…
A Systematic Security Evaluation of OpenClaw and Its Variants
Yuhang Wang, Haichang Gao, Zhenxing Niu +4
Tool-augmented AI agents substantially extend the practical capabilities of large language models, but they also introduce security risks that cannot be identified through model-on…
From Assistant to Double Agent: Formalizing and Benchmarking Attacks on OpenClaw for Personalized Local AI Agent
Yuhang Wang, Feiming Xu, Zheng Lin +6
Although large language model (LLM)-based agents, exemplified by OpenClaw, are increasingly evolving from task-oriented systems into personalized AI assistants for solving complex…
Robust MLLM Unlearning via Visual Knowledge Distillation
Yuhang Wang, Zhenxing Niu, Haoxuan Ji +3
Recently, machine unlearning approaches have been proposed to remove sensitive information from well-trained large models. However, most existing methods are tailored for LLMs, whi…