The paper introduces AspGap, a novel method for inferring stellar labels from low-resolution spectra obtained from the Gaia XP mission. By utilizing a neural-network based regression model trained on APOGEE spectra, AspGap provides precise estimates of [$\alpha$/M], contributing to our understanding of the formation and chemo-dynamics of the Milky Way. The release of the AspGap codebase and stellar parameter catalog enables researchers to gain valuable insights into the Galaxy's evolution.
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