FIMP: Foundation Model-Informed Message Passing for Graph Neural Networks

arXiv:2210.09475v3 Announce Type: replace
Abstract: Foundation models have revolutionized the landscape of Deep Learning (DL), serving as a versatile platform which can be adapted to a wide range of downstream tasks. Despite their adaptability, applications of foundation models to downstream graph-based tasks have been limited, and there remains no convenient way to leverage large-scale non-graph pretrained models in graph-structured settings. In this work, we present a new framework which we term Foundation-Informed Message Passing (FIMP) to bridge the fields of …

abstract adaptability applications arxiv cs.lg deep learning foundation foundation model graph graph-based graph neural networks landscape networks neural networks platform tasks type