DeKoR: Decomposed Knowledge Routing for Efficient GNN--LLM Fusion
DeKoR proposes a method to efficiently combine Graph Neural Networks (GNNs) and Large Language Models (LLMs) by breaking down LLM knowledge into local and global views. It distills these views into lightweight experts that don't need the LLM during use. A node-adaptive router then intelligently combines predictions from these experts, improving accuracy while significantly reducing computational cost.