Relational In-Context Learning via Synthetic Pre-training with Structural Prior 事件

Relational In-Context Learning via Synthetic Pre-training with Structural Prior arXiv:2603.03805v5 Announce Type: replace-cross Abstract: Relational Databases (RDBs) are the backbone of modern business, yet they lack foundation models comparable to those in text or vision. A key obstacle is that high-quality RDBs are private, scarce, and structurally heterogeneous, making internet-scale pre-training infeasible. To overcome this data scarcity, we introduce RDB-PFN, the first relational foundatio