TaLK: Text-attributed Graph Dataset Distillation via Coupling Language Model with Graph-Aware Kernel

Text-attributed graphs (TAGs) are widely used in many real-world domains, and learning on TAGs requires jointly modeling text semantics and graph structure. A standard approach for modeling TAGs is to combine a language model (LM) and a graph neural network (GNN), but joint training is computational