We applied the improvement cycle methodology, previously used for the ZINC dataset, to PubChem. This involved generating molecular analogs via the Mol2Mol model, simulating spectral data, and fine-tuning the model (details in Methods section). For comparison, we also fine-tuned the ZINC-trained MMT model on the entire PubChem training set (referred to as PC-FT), allowing us to assess the effectiveness of our targeted improvement cycles against a more comprehensive fine-tuning approach.