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PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models

arXiv:2609.23574v1 Announce Type: new Abstract: In high-dimensional tabular learning, feature screening provides a lightweight, model-agnostic way to remove irrelevant features before model fitting. However, scoring raw values directly can miss nonlinear or distributional structure. We introduce PA…

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  1. 2026-09-22 04:00 · arXiv stat.ML
    PACE: Plug-and-Play Contextual Embedding for Feature Screening with Pretrained Tabular Foundation Models

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