A pretrained foundation model built for table data and reused on new tables.
Think of a spreadsheet whiz who has read every budget sheet in town. Give it a new table, and it spots the columns before grabbing a calculator.
It helps predict numbers. It helps check risk. It helps teams study daily work. It can start with fewer hand-made features.
Foundation-model
A Tabular Foundation Model uses large pretraining first, then moves to new tables.
Feature-engineering
It tries to learn rows and columns, so people make fewer features by hand.
XGBoost
XGBoost is the old champ for table prediction and a key benchmark.
Transformer
Many Tabular Foundation Models use Transformers to read rows and columns.