Author

David Holzmüller

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#machine learning May 2026

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image

This work introduces MulTaBench, a benchmark of 40 datasets, split equally between image-tabular and text-tabular tasks, designed to enable the research of novel architectures which incorporate joint modeling and target-aware representations, paving the way for the development of novel Multimodal Tabular Foundation Mod...

Alan Arazi, Eilam Shapira, Shoham Grunblat et al. · arXiv.org · 3 citations

#machine learning Feb 2026

TabICLv2: A better, faster, scalable, and open tabular foundation model

TabICLv2 is introduced, a new state-of-the-art foundation model for regression and classification built on three pillars: a novel synthetic data generation engine designed for high pretraining diversity, various architectural innovations, and optimized pretraining protocols, notably replacing AdamW with the Muon optimi...

Jingang Qu, David Holzmüller, G. Varoquaux et al. · arXiv.org · 159 citations · ⚡44