18 citations · 19 across the 9 of their papers we have counts for
11 papers
Unveiling Spectral Mechanisms in Training-Free LLM Text Detection
Haitong Luo, Xuying Meng, Weiyao Zhang +5
The rapid advancement of Large Language Models (LLMs) makes it increasingly difficult to distinguish human writing from machine-generated text. Training-free detection offers a sca…
Nethira: A Heterogeneity-aware Hierarchical Pre-trained Model for Network Traffic Classification
Chungang Lin, Weiyao Zhang, Haitong Luo +2
Network traffic classification is vital for network security and management. The pre-training technology has shown promise by learning general traffic representations from raw byte…
Heterogeneity-Oblivious Robust Federated Learning
Weiyao Zhang, Jinyang Li, Qi Song +5
Federated Learning (FL) remains highly vulnerable to poisoning attacks, especially under real-world hyper-heterogeneity, where clients differ significantly in data distributions, c…
Distillation-Enhanced Clustering Acceleration for Encrypted Traffic Classification
Ziyue Huang, Chungang Lin, Weiyao Zhang +2
Traffic classification plays a significant role in network service management. The advancement of deep learning has established pretrained models as a robust approach for this task…
SpecDetect: Simple, Fast, and Training-Free Detection of LLM-Generated Text via Spectral Analysis
Haitong Luo, Weiyao Zhang, Suhang Wang +4
The proliferation of high-quality text from Large Language Models (LLMs) demands reliable and efficient detection methods. While existing training-free approaches show promise, the…
Aligning the Spectrum: Hybrid Graph Pre-training and Prompt Tuning across Homophily and Heterophily
Haitong Luo, Suhang Wang, Weiyao Zhang +3
Graph ``pre-training and prompt-tuning'' aligns downstream tasks with pre-trained objectives to enable efficient knowledge transfer under limited supervision. However, current meth…
Versatile yet Efficient Network Traffic Analysis: Offloading Network Foundation Model to SmartNIC
Chungang Lin, Xuying Meng, Tianyu Zuo +9
Pervasive encryption makes large-scale labeling infeasible for traffic analysis, while security operations demand edge analysis to avert service degradation and further vulnerabili…
TraGe: A Generic Packet Representation for Traffic Classification Based on Header-Payload Differences
Chungang Lin, Yilong Jiang, Weiyao Zhang +3
Traffic classification has a significant impact on maintaining the Quality of Service (QoS) of the network. Since traditional methods heavily rely on feature extraction and large s…
Enhance Graph Alignment for Large Language Models
Haitong Luo, Xuying Meng, Suhang Wang +4
Graph-structured data is prevalent in the real world. Recently, due to the powerful emergent capabilities, Large Language Models (LLMs) have shown promising performance in modeling…
Spectral-Based Graph Neural Networks for Complementary Item Recommendation
Haitong Luo, Xuying Meng, Suhang Wang +4
Modeling complementary relationships greatly helps recommender systems to accurately and promptly recommend the subsequent items when one item is purchased. Unlike traditional simi…
NetGPT: Generative Pretrained Transformer for Network Traffic
Xuying Meng, Chungang Lin, Yequan Wang +1
All data on the Internet are transferred by network traffic, thus accurately modeling network traffic can help improve network services quality and protect data privacy. Pretrained…