2 papers
cs.LG2025
Glance for Context: Learning When to Leverage LLMs for Node-Aware GNN-LLM Fusion
Donald Loveland, Yao-An Yang, Danai Koutra
Learning on text-attributed graphs has motivated the use of Large Language Models (LLMs) for graph learning. However, most fusion strategies are applied uniformly across all nodes…
cs.LG2024
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
Jiong Zhu, Gaotang Li, Yao-An Yang +3
Heterophily, or the tendency of connected nodes in networks to have different class labels or dissimilar features, has been identified as challenging for many Graph Neural Network…