8 papers
DMark: Order-Agnostic Watermarking for Diffusion Large Language Models
Linyu Wu, Linhao Zhong, Wenjie Qu +5
Diffusion large language models (dLLMs) offer faster generation than autoregressive models while maintaining comparable quality, but existing watermarking methods fail on them due…
RepoMark: A Data-Usage Auditing Framework for Code Large Language Models
Wenjie Qu, Yuguang Zhou, Bo Wang +4
The rapid development of Large Language Models (LLMs) for code generation has transformed software development by automating coding tasks with unprecedented efficiency. However, th…
ExtendAttack: Attacking Servers of LRMs via Extending Reasoning
Zhenhao Zhu, Yue Liu, Zhiwei Xu +9
Large Reasoning Models (LRMs) have demonstrated promising performance in complex tasks. However, the resource-consuming reasoning processes may be exploited by attackers to malicio…
Efficient Reasoning via Chain of Unconscious Thought
Ruihan Gong, Yue Liu, Wenjie Qu +11
Large Reasoning Models (LRMs) achieve promising performance but compromise token efficiency due to verbose reasoning processes. Unconscious Thought Theory (UTT) posits that complex…
Prompt Inversion Attack against Collaborative Inference of Large Language Models
Wenjie Qu, Yuguang Zhou, Yongji Wu +4
Large language models (LLMs) have been widely applied for their remarkable capability of content generation. However, the practical use of open-source LLMs is hindered by high reso…
Silent Leaks: Implicit Knowledge Extraction Attack on RAG Systems through Benign Queries
Yuhao Wang, Wenjie Qu, Shengfang Zhai +5
Retrieval-Augmented Generation (RAG) systems enhance large language models (LLMs) by incorporating external knowledge bases, but this may expose them to extraction attacks, leading…