2026ApJ...998..307Z

Red supergiants (RSGs), representing a kind of massive young stellar population, have rarely been used to probe the structure of the Milky Way, mainly due to the long-standing scarcity of Galactic RSG samples. The Gaia BP/RP spectra (hereafter XP), which cover a broad wavelength range, provide a powerful tool for identifying RSGs. In this work, we develop a feedforward neural network classifier that assigns to each XP spectrum a probability of being an RSG, denoted as P(RSG). We perform 10 independent runs with randomly divided training and validation sets, and apply each run to all XP spectra of stars with G < 12 mag. By selecting sources with P(RSG) ≥ 0.9, 10 high-confidence candidate samples are obtained. A star is considered a true Galactic RSG only if it appears in at least eight of these samples, yielding a final catalog of 2436 objects. These RSGs show a clear spatial correlation with OB stars and trace the Galactic spiral arms well, confirming the reliability of our classification, and highlighting their potential to serve as powerful tracers of the Milky Way's structure.