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Image Credit: Arxiv

On Finetuning Tabular Foundation Models

  • Foundation models in tabular deep learning are a new area of focus.
  • Recent research highlighted TabPFNv2's superior performance over traditional methods on small datasets.
  • Full finetuning is found to be the most effective approach for adapting TabPFNv2, improving time-efficiency and effectiveness.
  • Finetuning alters TabPFNv2's internal mechanisms, enhancing similarity accuracy and improving prediction logic.

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