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papersTODAY 04:00 UTC

arXiv Paper Examines Whether Tabular Foundation Models Still Require Feature Engineering

A new arXiv preprint in machine learning asks whether manual feature engineering remains necessary now that tabular foundation models exist. These models are pretrained across many tabular datasets and applied through in-context learning, which may reduce reliance on hand-crafted features. The abstract frames the question as an open issue for tabular machine learning research.

arXiv feature engineering in-context learning pretraining tabular machine learning tabular-foundation-models

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arXiv cs.LGDo Tabular Foundation Models Still Need Feature Engineering? ↗TODAY 04:00 UTC