collaborators

5 papers

cs.CR2026

CI-Work: Benchmarking Contextual Integrity in Enterprise LLM Agents

Wenjie Fu, Xiaoting Qin, Jue Zhang +5

Enterprise LLM agents can dramatically improve workplace productivity, but their core capability, retrieving and using internal context to act on a user's behalf, also creates new…

cs.NI2025

Tutorial on Large Language Model-Enhanced Reinforcement Learning for Wireless Networks

Lingyi Cai, Wenjie Fu, Yuxi Huang +9

Reinforcement Learning (RL) has shown remarkable success in enabling adaptive and data-driven optimization for various applications in wireless networks. However, classical RL suff…

cs.CL2025

Rethinking LLM Evaluation: Can We Evaluate LLMs with 200x Less Data?

Shaobo Wang, Cong Wang, Wenjie Fu +11

As the demand for comprehensive evaluations of diverse model capabilities steadily increases, benchmark suites have correspondingly grown significantly in scale. Despite notable ad…

cs.CL2025

Sanitize Your Responses: Mitigating Privacy Leakage in Large Language Models

Wenjie Fu, Huandong Wang, Junyao Gao +2

As Large Language Models (LLMs) achieve remarkable success across a wide range of applications, such as chatbots and code copilots, concerns surrounding the generation of harmful c…

cs.AI2025

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy

Huandong Wang, Wenjie Fu, Yingzhou Tang +7

While large language models (LLMs) present significant potential for supporting numerous real-world applications and delivering positive social impacts, they still face significant…