59 citations · 64 across the 10 of their papers we have counts for
11 papers
SPFR: Semantic Potential Field Routing for the Distributed Internet of Agents
Yeguang Qin, Liangqi Peng, Fengxiao Tang +1
In a distributed Internet of Agents (IoA) without centralized routing control, routing tasks to capability-matched executors is challenging because destinations are not predetermin…
PropLLM: Propagation-Aware Scene Reconstruction for Network Fault Diagnosis
Zongzong Wu, Ming Zhao, Fengxiao Tang +1
Network faults propagate layer by layer along topology and protocol dependencies, yet operations systems typically observe only symptomatic alerts at the tail end of propagation ch…
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…
FaultDiffusion: Few-Shot Fault Time Series Generation with Diffusion Model
Yi Xu, Zhigang Chen, Rui Wang +4
In industrial equipment monitoring, fault diagnosis is critical for ensuring system reliability and enabling predictive maintenance. However, the scarcity of fault data, due to the…
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…
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…
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…
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…
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…
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…
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…