activity
20212026
most cited6G comprehensive intelligence: network operations and optimization based on Large Language Models

59 citations · 67 across the 9 of their papers we have counts for

collaborators

10 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.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.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…

cs.NI2025

Adapting Network Information into Semantics for Generalizable and Plug-and-Play Multi-Scenario Network Diagnosis

Tiao Tan, Fengxiao Tang, Linfeng Luo +3

Leverage large language model (LLM) to refer the fault is considered to be a potential solution for intelligent network fault diagnosis. However, how to represent network informati…

cs.CR2024

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.LG2024

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.NI2024★ 5 cited

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.NI2024★ 59 cited

6G comprehensive intelligence: network operations and optimization based on Large Language Models

Sifan Long, Fengxiao Tang, Yangfan Li +4

The sixth generation mobile communication standard (6G) can promote the development of Industrial Internet and Internet of Things (IoT). To achieve comprehensive intelligent develo…

cs.CL2022★ 1 cited

EmoCaps: Emotion Capsule based Model for Conversational Emotion Recognition

Zaijing Li, Fengxiao Tang, Ming Zhao +1

Emotion recognition in conversation (ERC) aims to analyze the speaker's state and identify their emotion in the conversation. Recent works in ERC focus on context modeling but igno…

cs.CL2021★ 2 cited

SEOVER: Sentence-level Emotion Orientation Vector based Conversation Emotion Recognition Model

Zaijing Li, Fengxiao Tang, Tieyu Sun +2

For the task of conversation emotion recognition, recent works focus on speaker relationship modeling but ignore the role of utterance's emotional tendency.In this paper, we propos…