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#machine learning Preprint Sep 2026

Support-Compiled Feature Folding: More Evidence at Lower Memory Across Tabular Foundation Models

Wide tables offer tabular foundation models more evidence, but accessing it can exhaust their memory: full-width pairwise mixing grows quadratically with the number of columns, while feature selection makes inputs affordable by discarding evidence. We ask whether using more features requires interacting over all of the...

Tian Zhou, Beverly Jin, Xue Wang et al. · 0 citations

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