collaborators

8 papers

cs.CV2026

ClawMark: A Living-World Benchmark for Multi-Turn, Multi-Day, Multimodal Coworker Agents

Fanqing Meng, Lingxiao Du, Zijian Wu +46

Language-model agents are increasingly used as persistent coworkers that assist users across multiple working days. During such workflows, the surrounding environment may change in…

cs.CL2026

DiffuGuard: How Intrinsic Safety is Lost and Found in Diffusion Large Language Models

Zherui Li, Zheng Nie, Zhenhong Zhou +7

The rapid advancement of Diffusion Large Language Models (dLLMs) introduces unprecedented vulnerabilities that are fundamentally distinct from Autoregressive LLMs, stemming from th…

cs.CR2026

IMMACULATE: A Practical LLM Auditing Framework via Verifiable Computation

Yanpei Guo, Wenjie Qu, Linyu Wu +7

Commercial large language models are typically deployed as black-box API services, requiring users to trust providers to execute inference correctly and report token usage honestly…

cs.CR2025

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…

cs.LG2025

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…

cs.CR2025

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…