2026-08-12 · 2608.10280v1
Raquel R. Valença, Lilianne Nakazono, Rafael Izbicki, et al.
This paper tests whether frozen tabular foundation models can deliver full probabilistic quasar photo-z posteriors for the 12-band S-PLUS DR6 survey, where colour-redshift degeneracies and spectroscopic-to-photometric covariate shift make single-value estimates inadequate. Across training sets spanning 500 to 121,626 quasars and comparisons with eight specialised baselines, TabPFN 2.5 is best or statistically tied for best on nearly every density and point-estimation metric, with especially strong gains for small training samples, bright or faint sources, and high-redshift quasars. Its posteriors remain close to nominally calibrated after importance-weighted evaluation intended to emulate the photometric target catalogue, making it a strong default for catalogue-scale quasar redshift inference; the practical limitation is the accelerator-memory cost of inference on large support and target sets. SHAP results further identify WISE W1/W2 as the most informative individual inputs, with UV and optical bands providing useful refinements.