12 papers
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…
Salami Attack: Stealthy Collusive Memory Poisoning against OpenClaw
Zheng Lin, Yuzhe Huang, Zhenxing Niu +2
Long-term memory enables LLM agents to retain useful information across sessions, but also creates an attack surface through which adversaries may poison an agent's persistent memo…
Attention-Guided Reward for Reinforcement Learning-based Jailbreak against Large Reasoning Models
Zheng Lin, Zhenxing Niu, Haoxuan Ji +2
Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in solving complex problems by generating structured, step-by-step reasoning content. However, exposing a mo…
Re-Triggering Safeguards within LLMs for Jailbreak Detection
Zheng Lin, Zhenxing Niu, Haoxuan Ji +2
This paper proposes a jailbreaking prompt detection method for large language models (LLMs) to defend against jailbreak attacks. Although recent LLMs are equipped with built-in saf…
Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing
Zheng Lin, Zhenxing Niu, Haoxuan Ji +1
This paper proposes a guaranteed defense method for large language models (LLMs) to safeguard against jailbreaking attacks. Drawing inspiration from the denoised-smoothing approach…
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…