TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks

Researchers introduced TabPrep, a lightweight preprocessing pipeline for tabular feature engineering.

On TabArena, adding TabPrep improved results across tree-based, neural, linear, and foundation models.

The gains often exceeded model-only improvements and beat earlier automated feature engineering methods on efficiency and coverage.

The work highlights how preprocessing can meaningfully change tabular benchmark outcomes.