Mochi: Aligning Pre-training and Inference for Efficient Graph Foundation Models via Meta-Learning

Mochi is a Graph Foundation Model that improves efficiency and task unification by employing a meta-learning based training framework. It pre-trains on few-shot episodes directly mirroring downstream evaluation, addressing limitations of traditional reconstruction-based pre-training and achieving competitive performance.