15 citations · 18 across the 7 of their papers we have counts for
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cs.LG2024
FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks
Renqiang Luo, Huafei Huang, Shuo Yu +4
Fairness-aware Graph Neural Networks (GNNs) often face a challenging trade-off, where prioritizing fairness may require compromising utility. In this work, we re-examine fairness t…
cs.LG2024
FairGT: A Fairness-aware Graph Transformer
Renqiang Luo, Huafei Huang, Shuo Yu +2
The design of Graph Transformers (GTs) generally neglects considerations for fairness, resulting in biased outcomes against certain sensitive subgroups. Since GTs encode graph info…
cs.AI2024★ 15 cited
Deep Outdated Fact Detection in Knowledge Graphs
Huiling Tu, Shuo Yu, Vidya Saikrishna +2
Knowledge graphs (KGs) have garnered significant attention for their vast potential across diverse domains. However, the issue of outdated facts poses a challenge to KGs, affecting…