108 citations · 108 across the 3 of their papers we have counts for
3 papers
cs.LG2026
HeterSEED: Semantics-Structure Decoupling for Heterogeneous Graph Learning under Heterophily
Xinyi Li, Ming Li, Lu Bai +5
Many real-world heterogeneous graphs exhibit pronounced heterophily, where connected nodes often have dissimilar labels or play different semantic roles. In such settings, standard…
cs.LG2025
Out-of-Distribution Detection on Graphs: A Survey
Tingyi Cai, Yunliang Jiang, Yixin Liu +3
Graph machine learning has witnessed rapid growth, driving advancements across diverse domains. However, the in-distribution assumption, where training and testing data share the s…
cs.LG2022★ 108 cited
Graph Neural Networks for Graphs with Heterophily: A Survey
Xin Zheng, Yi Wang, Yixin Liu +5
Recent years have witnessed fast developments of graph neural networks (GNNs) that have benefited myriad graph analytic tasks and applications. Most GNNs rely on the homophily assu…