TabFM: A Zero-Shot Foundation Model for Tabular Data
TabFM, a 400M-parameter tabular foundation model that formulates supervised tabular prediction as in-context learning, produces calibrated zero-shot predictions in a single forward pass without task-specific tuning.
Wei-Hao Kong, Erez Louidor Ilan, Shu-Xin Nie et al.
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