activity
20222024
most citedSpace4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network

34 citations · 65 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2024★ 1 cited

Advancing Molecular Graph-Text Pre-training via Fine-grained Alignment

Yibo Li, Yuan Fang, Mengmei Zhang +1

Understanding molecular structure and related knowledge is crucial for scientific research. Recent studies integrate molecular graphs with their textual descriptions to enhance mol…

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.SI2023

A Generalized Neural Diffusion Framework on Graphs

Yibo Li, Xiao Wang, Hongrui Liu +1

Recent studies reveal the connection between GNNs and the diffusion process, which motivates many diffusion-based GNNs to be proposed. However, since these two mechanisms are close…

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…