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TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14

The claim behind TabPFN and TabICL is that they predict on a table without ever training on it and still beat tuned boosting.

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TabPFN and TabICL vs. tuned XGBoost: the model that doesn't train won 14/14

Owned by efraingaray.com. Added September 27, 2026 at 11:45 PM EDT.

The claim behind TabPFN and TabICL is that they predict on a table without ever training on it and still beat tuned boosting.

Marked as found on the page, exactly, September 28, 2026 at 11:30 PM EDT. The check history below is the evidence.

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WhenCheckResultStatusDetail
September 27, 2026 at 11:45 PM EDTLink resolvesPassed200200, text/html, 117452 characters, landed on https://efraingaray.com/en/blog/tabpfn-vs-xgboost/
September 27, 2026 at 11:45 PM EDTPage contains the quotationPassed200the page contains the quotation, exactly

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