4 citations · 5 across the 7 of their papers we have counts for
8 papers
VulInstruct: Teaching LLMs Root-Cause Reasoning for Vulnerability Detection via Security Specifications
Hao Zhu, Jia Li, Cuiyun Gao +7
Large language models (LLMs) have achieved remarkable progress in code understanding tasks. However, they demonstrate limited performance in vulnerability detection and struggle to…
VulAgent: Hypothesis-Validation based Multi-Agent Vulnerability Detection
Ziliang Wang, Ge Li, Jia Li +2
The application of language models to project-level vulnerability detection remains challenging, owing to the dual requirement of accurately localizing security-sensitive code and…
QoSBERT: An Uncertainty-Aware Approach based on Pre-trained Language Models for Service Quality Prediction
Ziliang Wang, Xiaohong Zhang, Ze Shi Li +1
Accurate prediction of Quality of Service (QoS) metrics is fundamental for selecting and managing cloud based services. Traditional QoS models rely on manual feature engineering an…
M2CVD: Enhancing Vulnerability Semantic through Multi-Model Collaboration for Code Vulnerability Detection
Ziliang Wang, Ge Li, Jia Li +3
Large Language Models (LLMs) have strong capabilities in code comprehension, but fine-tuning costs and semantic alignment issues limit their project-specific optimization; converse…
Line-level Semantic Structure Learning for Code Vulnerability Detection
Ziliang Wang, Ge Li, Jia Li +3
Unlike the flow structure of natural languages, programming languages have an inherent rigidity in structure and grammar.However, existing detection methods based on pre-trained mo…
Dual Latent State Learning: Exploiting Regional Network Similarities for QoS Prediction
Ziliang Wang, Xiaohong Zhang, Kechi Zhang +2
Individual objects, whether users or services, within a specific region often exhibit similar network states due to their shared origin from the same city or autonomous system (AS)…
Feature Noise Resilient for QoS Prediction with Probabilistic Deep Supervision
Ziliang Wang, Xiaohong Zhang, Ze Shi Li +2
Accurate Quality of Service (QoS) prediction is essential for enhancing user satisfaction in web recommendation systems, yet existing prediction models often overlook feature noise…
A Probability Distribution and Location-aware ResNet Approach for QoS Prediction
Wenyan Zhang, Ling Xu, Meng Yan +2
In recent years, the number of online services has grown rapidly, invoke the required services through the cloud platform has become the primary trend. How to help users choose and…