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One Thousand Galaxies Beat a Bespoke Forty Thousand
A tabular foundation model matched or exceeded photometric-redshift baselines trained on more than 40,000 galaxies using 1,000 in-context examples.
Summary
A tabular foundation model matched or exceeded photometric-redshift baselines trained on more than 40,000 galaxies using 1,000 in-context examples.
Astronomers estimate galaxy distance from imaging when spectroscopy is scarce, but training samples are biased toward bright, easy targets. In benchmark tests, tabular foundation models predicted full redshift distributions in one pass and matched or exceeded bespoke estimators trained on more than 40,000 galaxies while using 1,000 in-context examples. Their advantage was largest with little calibration data and persisted after baselines received as many as 10,000 representative spectra. The claim is benchmark-specific and does not remove the need to test survey-specific selection effects.
Why it matters
A tabular foundation model matched or exceeded photometric-redshift baselines trained on more than 40,000 galaxies using 1,000 in-context examples.
Limits and context
- The claim is benchmark-specific and does not remove the need to test survey-specific selection effects.
Key claims
A tabular foundation model matched or exceeded photometric-redshift baselines trained on more than 40,000 galaxies using 1,000 in-context examples.
Qualification: The claim is benchmark-specific and does not remove the need to test survey-specific selection effects.
Evidence: source-2026-10-31-014
Sources
- arXiv preprint 2610.39332, original v1arXiv · primary research
Corrections
No corrections have been recorded for this story.