2 papers
cs.LG2026
TICDA: Tabular In-Context Data Attribution
Yacine Benihaddadene, Milan Bhan, Eliot Dugelay +4
Tabular foundation models (TFMs) achieve strong predictive performance by conditioning on labeled demonstrations provided in context, without any parameter update. Yet how individu…
cs.LG2026
TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models
Duong Nguyen, Mohammed Jawhar, Nicolas Chesneau
Tabular foundation models (TFMs), such as TabPFN-2.6, TabICLv2, ConTextTab, Mitra, LimiX, and TabDPT, achieve strong zero-shot performance through in-context learning, but their in…