2 citations · 5 across the 13 of their papers we have counts for
4 papers · 1 filter
LangGFM: A Large Language Model Alone Can be a Powerful Graph Foundation Model
Tianqianjin Lin, Pengwei Yan, Kaisong Song +7
Graph foundation models (GFMs) have recently gained significant attention. However, the unique data processing and evaluation setups employed by different studies hinder a deeper u…
Empowering Dual-Level Graph Self-Supervised Pretraining with Motif Discovery
Pengwei Yan, Kaisong Song, Zhuoren Jiang +4
While self-supervised graph pretraining techniques have shown promising results in various domains, their application still experiences challenges of limited topology learning, hum…
Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph
Tianqianjin Lin, Kaisong Song, Zhuoren Jiang +6
Heterogeneous graph neural networks have become popular in various domains. However, their generalizability and interpretability are limited due to the discrepancy between their in…
Community-Based Hierarchical Positive-Unlabeled (PU) Model Fusion for Chronic Disease Prediction
Yang Wu, Xurui Li, Xuhong Zhang +3
Positive-Unlabeled (PU) Learning is a challenge presented by binary classification problems where there is an abundance of unlabeled data along with a small number of positive data…