1. Introduction
2. Observation and data
2.1. Training and observed sample
2.2. Pre-processing training and observed sample
2.3. The t-SNE method for homogeneity check and outlier detections
3. Convolutional neural network for stellar parameterization
3.2. Training the CNN
4. Catalog of stellar parameters & Li abundances
4.1. CNN parameterization of the GES GIRAFFE spectra
5. Validation of CNN predictions
5.1. Validation with Gaia benchmark Stars
6. Constraining the chemical evolution of lithium in the Milky Way
6.1. Galactic evolution of lithium
7. Summary and future prospects