4 papers
GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion
Qizhuo Xie, Yunhui Liu, Yu Xing +4
Large Language Models (LLMs) have shown immense potential in Knowledge Graph Completion (KGC), yet bridging the modality gap between continuous graph embeddings and discrete LLM to…
Mitigating Homophily Disparity in Graph Anomaly Detection: A Scalable and Adaptive Approach
Yunhui Liu, Qizhuo Xie, Yinfeng Chen +4
Graph anomaly detection (GAD) aims to identify nodes that deviate from normal patterns in structure or features. While recent GNN-based approaches have advanced this task, they str…
Towards Anomaly-Aware Pre-Training and Fine-Tuning for Graph Anomaly Detection
Yunhui Liu, Jiashun Cheng, Yiqing Lin +7
Graph anomaly detection (GAD) has garnered increasing attention in recent years, yet remains challenging due to two key factors: (1) label scarcity stemming from the high cost of a…
Multi-Scale Heterogeneous Text-Attributed Graph Datasets From Diverse Domains
Yunhui Liu, Qizhuo Xie, Jinwei Shi +2
Heterogeneous Text-Attributed Graphs (HTAGs), where different types of entities are not only associated with texts but also connected by diverse relationships, have gained widespre…