Elite-Weighted Supervised Fine-tuning for Goal-Directed Molecular Optimization

Goal-directed optimization is essential for steering molecular generators to propose candidates with desired properties. However, it is often implemented with policy-gradient reinforcement learning, which requires a generation-trajectory log-probability whose form depends on the model architecture a