38 citations · 39 across the 7 of their papers we have counts for
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cs.AI2026
What Makes a Desired Graph for Relational Deep Learning?
Yao Cheng, Siqiang Luo
Relational deep learning (RDL) converts relational databases (RDBs) into heterogeneous graphs, but graphs derived directly from database schemas are often not well suited for how g…
cs.AI2024
SEAGraph: Unveiling the Whole Story of Paper Review Comments
Jianxiang Yu, Jiaqi Tan, Zichen Ding +7
Peer review, as a cornerstone of scientific research, ensures the integrity and quality of scholarly work by providing authors with objective feedback for refinement. However, in t…
cs.AI2024★ 1 cited
Can Large Language Models Act as Ensembler for Multi-GNNs?
Hanqi Duan, Yao Cheng, Jianxiang Yu +2
Graph Neural Networks (GNNs) have emerged as powerful models for learning from graph-structured data. However, GNNs lack the inherent semantic understanding capability of rich text…