AI RESEARCH
Distilling Tabular Foundation Models for Structured Health Data
arXiv CS.LG
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ArXi:2605.18702v1 Announce Type: new Tabular foundation models (TFMs) achieve strong performance on health datasets, but their inference cost and infrastructure requirements limit practical use. We study whether their predictive behavior can be transferred to lightweight tabular models through knowledge distillation. Since in-context TFMs condition on the