GP-MoLFormer: a foundation model for molecular generation
Jerret Ross, Brian M. Belgodere, Samuel C. Hoffman, Vijil Chenthamarakshan, Jiri Navratil, Youssef Mroueh, Payel Das · Digital Discovery · 2025
GP-MoLFormer, a GPT-style chemical foundation model trained on 0.65–1.1b SMILES, reveals the impact of training and inference scaling on generation quality. With pair-tuning, a novel fine-tuning method, it enables efficient molecular optimization.