collaborators

8 papers

cs.CL2026

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…

cs.NI2026

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…

cs.LG2025

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…

cs.NI2025

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…

cs.CL2025

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…

cs.LG2025

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…

cs.NI2025

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…

cs.NI2025

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…