Do tabular foundation models repair themselves?

LessWrong reports that researchers examined four state‑of‑the‑art tabular foundation models across fifteen binary classification tasks to see if they can self‑repair after component ablation. While large language models often compensate for damaged parts, the experiments found little evidence of such self‑repair in the tabular models, with redundancy appearing more likely. The authors conclude that ablation studies on these models should be interpreted as revealing overlapping functionality rather than hidden repair mechanisms.

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