collaborators

8 papers

cs.NI2026

Toward Realistic Wi-Fi Fault Diagnosis: A Multi-Modal Benchmark

Junjian Zhang, Haobo Deng, Xinxin Li +3

Intelligent network operation and maintenance systems in modern networks continuously generate large volumes of multi-modal operational data. However, Wi-Fi fault diagnosis under h…

cs.NI2026

MSADM: Large Language Model (LLM) Assisted End-to-End Network Health Management Based on Multi-Scale Semanticization

Fengxiao Tang, Xiaonan Wang, Xun Yuan +4

Network device and system health management is the foundation of modern network operations and maintenance. Traditional health management methods, relying on expert identification…

cs.CL2025

Chain or tree? Re-evaluating complex reasoning from the perspective of a matrix of thought

Fengxiao Tang, Yufeng Li, Zongzong Wu +1

Large Language Models (LLMs) face significant accuracy degradation due to insufficient reasoning ability when dealing with complex and abstract tasks. Thought structures such as Ch…

cs.LG2025

Federated Hypergraph Learning with Local Differential Privacy: Toward Privacy-Aware Hypergraph Structure Completion

Linfeng Luo, Zhiqi Guo, Fengxiao Tang +2

The rapid growth of graph-structured data necessitates partitioning and distributed storage across decentralized systems, driving the emergence of federated graph learning to colla…

cs.CR2025

KGV: Integrating Large Language Models with Knowledge Graphs for Cyber Threat Intelligence Credibility Assessment

Zongzong Wu, Fengxiao Tang, Ming Zhao +1

Cyber threat intelligence (CTI) is a crucial tool to prevent sophisticated, organized, and weaponized cyber attacks. However, few studies have focused on the credibility assessment…

cs.CR2025

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification

Fengxiao Tang, Huan Li, Ming Zhao +3

Verifying the credibility of Cyber Threat Intelligence (CTI) is essential for reliable cybersecurity defense. However, traditional approaches typically treat this task as a static…