34 citations · 65 across the 5 of their papers we have counts for
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cs.LG2024
Graph Fairness Learning under Distribution Shifts
Yibo Li, Xiao Wang, Yujie Xing +4
Graph neural networks (GNNs) have achieved remarkable performance on graph-structured data. However, GNNs may inherit prejudice from the training data and make discriminatory predi…
cs.LG2023★ 30 cited
Graph Foundation Models: Concepts, Opportunities and Challenges
Jiawei Liu, Cheng Yang, Zhiyuan Lu +8
Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and seve…
cs.LG2022★ 34 cited
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network
Tianyu Zhao, Cheng Yang, Yibo Li +7
Heterogeneous Graph Neural Network (HGNN) has been successfully employed in various tasks, but we cannot accurately know the importance of different design dimensions of HGNNs due…