Google TabFM predicts on unseen tables

Google Research proposes TabFM, a foundation model that treats tabular prediction as in-context learning. It generates predictions for a new, unseen table in a single forward pass, skipping per-dataset training, hyperparameter tuning, feature engineering, and retraining pipelines.