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Tabular foundation models fail to grasp physics principles, study finds

A new research paper investigates whether tabular foundation models (TFMs) have learned physics principles from the data they are trained on. The study evaluated four TFMs, including TabPFN-3 and TabICLv2, against six baseline models using datasets derived from 316 physical equations. While the TFMs demonstrated strong performance, the research found they cannot represent noiseless mechanisms or physical units, limiting their ability to function as true physical models. AI

IMPACT This research highlights limitations in current tabular foundation models, suggesting further development is needed for them to truly understand and apply physical principles.

RANK_REASON Research paper published on arXiv detailing findings about tabular foundation models.

Read on Hugging Face Daily Papers →

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Tabular foundation models fail to grasp physics principles, study finds

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Research paper published on arXiv detailing findings about tabular foundation models.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Wassim Tenachi, Yashar Hezaveh, Laurence Perreault Levasseur, Pierre-Luc Bacon ·

    Do Tabular Foundation Models Know Physics? Contamination, Units, and the Deterministic Limit

    arXiv:2609.02766v1 Announce Type: new Abstract: Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text, and tables are arguably the format in which most physical measurement arrives. Did they learn any physics in the process? They are Bayesi…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Do Tabular Foundation Models Know Physics? Contamination, Units, and the Deterministic Limit

    Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text, and tables are arguably the format in which most physical measurement arrives. Did they learn any physics in the process? They are Bayesian by construction, so the question is what thei…