Architecture Alignment With Sparse Priors in Tabular Foundation Models
Tabular foundation models (TFMs) are increasingly popular because they deliver strong predictions on new datasets through in-context learning, without task-specific training or extensive tuning. Yet released TFMs differ simultaneously in their pretraining priors, architectures, and objectives, obscuring their respectiv...
Tian-Qi Zhao, Tian-Yi Zhuang, Shuo Duan et al.
· 0 citations