3 papers
cs.LG2024
CORE: Data Augmentation for Link Prediction via Information Bottleneck
Kaiwen Dong, Zhichun Guo, Nitesh V. Chawla
Link prediction (LP) is a fundamental task in graph representation learning, with numerous applications in diverse domains. However, the generalizability of LP models is often comp…
cs.LG2024
You do not have to train Graph Neural Networks at all on text-attributed graphs
Kaiwen Dong, Zhichun Guo, Nitesh V. Chawla
Graph structured data, specifically text-attributed graphs (TAG), effectively represent relationships among varied entities. Such graphs are essential for semi-supervised node clas…
cs.LG2024
Universal Link Predictor By In-Context Learning on Graphs
Kaiwen Dong, Haitao Mao, Zhichun Guo +1
Link prediction is a crucial task in graph machine learning, where the goal is to infer missing or future links within a graph. Traditional approaches leverage heuristic methods ba…