From the 1 of 4 linked papers with an AI index.
1 citations · 1 across the 2 of their papers we have counts for
4 papers
NodeImport: Imbalanced Node Classification with Node Importance Assessment
Nan Chen, Zemin Liu, Bryan Hooi +3
The paper proposes NodeImport, a framework that assesses node importance using a balanced meta-set to dynamically select valuable labeled, unlabeled, and synthetic nodes, improving…
Multi-Label Node Classification with Label Influence Propagation
Yifei Sun, Zemin Liu, Bryan Hooi +4
Graphs are a complex and versatile data structure used across various domains, with possibly multi-label nodes playing a particularly crucial role. Examples include proteins in PPI…
RGL: A Graph-Centric, Modular Framework for Efficient Retrieval-Augmented Generation on Graphs
Yuan Li, Jun Hu, Jiaxin Jiang +3
Recent advances in graph learning have paved the way for innovative retrieval-augmented generation (RAG) systems that leverage the inherent relational structures in graph data. How…
Partitioning Message Passing for Graph Fraud Detection
Wei Zhuo, Zemin Liu, Bryan Hooi +4
Label imbalance and homophily-heterophily mixture are the fundamental problems encountered when applying Graph Neural Networks (GNNs) to Graph Fraud Detection (GFD) tasks. Existing…