4 papers
UNIT: Unleash Large Language Models Potential for Graph Continual Learning
Tairan Huang, Yili Wang, Beibei Hu +4
In real-world multimodal web scenarios, graph-structured data often arrives in a streaming manner, making graph continual learning a crucial paradigm for continuously modeling such…
Detect by Yourself: Self-Designing Agentic Workflows for Few-Shot Graph Anomaly Detection
Tairan Huang, Qiang Chen, Yili Wang +4
Graph anomaly detection aims to identify anomaly nodes in attributed graphs and plays an important role in real-world applications. However, existing graph anomaly detection method…
Simple and Efficient Heterogeneous Temporal Graph Neural Network
Yili Wang, Tairan Huang, Changlong He +2
Heterogeneous temporal graphs (HTGs) are ubiquitous data structures in the real world. Recently, to enhance representation learning on HTGs, numerous attention-based neural network…
Can LLMs Find Fraudsters? Multi-level LLM Enhanced Graph Fraud Detection
Tairan Huang, Yili Wang, Qiutong Li +2
Graph fraud detection has garnered significant attention as Graph Neural Networks (GNNs) have proven effective in modeling complex relationships within multimodal data. However, ex…