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News/End-to-End Compression for Tabular Foundation Models
arxiv
PublishedJune 1, 2026 at 4:00 AM
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End-to-End Compression for Tabular Foundation Models

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Publisher summary· verbatim

arXiv:2602.05649v2 Announce Type: replace Abstract: The long-standing dominance of gradient-boosted decision trees for tabular data has recently been challenged by in-context learning tabular foundation models. In-context learning methods fit and predict in one forward pass without parameter updates

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