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Towards Foundation Database Models

Summary: Argues for foundation database models: pre-trained, dataset- and task-agnostic models that enable low-overhead transfer to unseen datasets and replace expensive one-off per-task training. Proposes an architecture, shows a prototype feasibility study, and outlines a research roadmap. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
559
Venue
CIDR
Year
2025
Pagerank
4.4371897e-05
Overall Rank
8,847 | 38.46%
DOI
-

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