5 papers
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…