LoGIC: Budgeted Context Construction for Node-Level Graph In-Context Learning with Tabular Foundation Models

Tabular foundation models have become powerful graph learners. Systems such as G2T-FM and GraphPFN encode each node as a feature row and make predictions through in-context learning (ICL), with labeled rows serving as the prompt. Current protocols employ the complete training table as context, causi