2025ApJS..281...58L

Precise stellar parameters for M-type stars, the Galaxy's most common stellar type, are crucial for numerous studies. In this work, we refined the LAMOST DR10 M-type star catalog through a two-stage process. First, we purified the catalog using techniques including deep learning and color-magnitude diagrams to remove 22,496 non-M spectra, corrected 2078 dwarf/giant classifications, and updated 12,900 radial velocities. This resulted in a cleaner catalog containing 870,518 M-type spectra (820,493 dwarfs, 50,025 giants). Second, applying a label transfer strategy using values from APOGEE DR16 for parameter prediction with a tenfold cross-validated convolutional neural network ensemble architecture, we predicted T_eff, $\mathrm{log}\,g$, [M/H], and [α/M] separately for M dwarfs (dMs) and giants (gMs). The average internal errors for dMs/gMs are, respectively, T_eff 30/17 K, log g 0.07/0.07 dex, [M/H] 0.07/0.05 dex, and [α/M] 0.02/0.02 dex. Comparison with APOGEE demonstrates external precisions of 34/14 K, 0.12/0.07 dex, 0.09/0.04 dex, and 0.03/0.02 dex for dMs/gMs, which represent precision improvements of over 20% for dMs and over 50% for gMs compared to previous literature results. The catalog is available at doi:10.12149/101668.