Author

Milan Bhan

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#artificial intelligence Preprint Oct 2026

The Standardization Trap: Certifying Joint Label Processing in Tabular Foundation Models

Linear regression and kernel smoothing offer tractable explanations of in-context learning: in both, the features determine the weight assigned to each context label. However, whether this fixed-weight account describes pretrained tabular foundation models (TFMs) remains unclear. Testing this account using derivatives...

Duong Nguyen, N. Chesneau, Milan Bhan · 0 citations

#artificial intelligence Preprint Oct 2026

TICDA: Tabular In-Context Data Attribution

Tabular foundation models (TFMs) achieve strong predictive performance by conditioning on labeled demonstrations provided in context, without any parameter update. Yet how individual demonstrations shape a given prediction remains poorly understood. This gap matters in practice: the context is often assembled from what...

Yacine Benihaddadene, Milan Bhan, Eliot Dugelay et al. · 0 citations