9 citations · 10 across the 5 of their papers we have counts for
7 papers
LoopTrap: Termination Poisoning Attacks on LLM Agents
Huiyu Xu, Zhibo Wang, Wenhui Zhang +4
Modern LLM agents solve complex tasks by operating in iterative execution loops, where they repeatedly reason, act, and self-evaluate progress to determine when a task is complete.…
DualBreach: Efficient Dual-Jailbreaking via Target-Driven Initialization and Multi-Target Optimization
Xinzhe Huang, Kedong Xiu, Tianhang Zheng +5
Recent research has focused on exploring the vulnerabilities of Large Language Models (LLMs), aiming to elicit harmful and/or sensitive content from LLMs. However, due to the insuf…
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models
Yu He, Boheng Li, Liu Liu +6
Membership Inference Attacks (MIAs) aim to predict whether a data sample belongs to the model's training set or not. Although prior research has extensively explored MIAs in Large…
Membership Inference Attacks Against Vision-Language Models
Yuke Hu, Zheng Li, Zhihao Liu +4
Vision-Language Models (VLMs), built on pre-trained vision encoders and large language models (LLMs), have shown exceptional multi-modal understanding and dialog capabilities, posi…
JailbreakLens: Interpreting Jailbreak Mechanism in the Lens of Representation and Circuit
Zeqing He, Zhibo Wang, Zhixuan Chu +4
Despite the outstanding performance of Large language Models (LLMs) in diverse tasks, they are vulnerable to jailbreak attacks, wherein adversarial prompts are crafted to bypass th…
A Certified Robust Watermark For Large Language Models
Xianheng Feng, Jian Liu, Kui Ren +1
The effectiveness of watermark algorithms in AI-generated text identification has garnered significant attention. Concurrently, an increasing number of watermark algorithms have be…
Combating Concept Drift with Explanatory Detection and Adaptation for Android Malware Classification
Yiling He, Junchi Lei, Zhan Qin +2
Machine learning-based Android malware classifiers achieve high accuracy in stationary environments but struggle with concept drift. The rapid evolution of malware, especially with…