2026
Glance for Context: Learning When to Leverage LLMs for Node-Aware GNN-LLM Fusion
ICLR 2026poster
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 and attain only small overall performance gains. We argue this result stems from aggregate metrics that obscure when LLM…