AI RESEARCH
RelPrism: A Multi-Faceted Pre-training Framework with Self-Generated Tasks for Relational Databases
arXiv CS.LG
•
ArXi:2605.23241v1 Announce Type: new Relational databases (RDBs) remain the cornerstone of modern data systems and diverse predictive tasks. Recent relational deep learning (RDL) methods enable end-to-end prediction by converting RDBs into graphs, where rows are represented as nodes and inter-table interactions are represented as edges, and then applying graph-based models for representation learning. Despite the strong capability of RDL, effective self-supervised pre-