We chose 64 parent molecules via K-means clustering (implemented in scikit-learn ) on the PCA embeddings to evaluate LLM performance on a diverse group of molecules. These so-called "parent molecules" were then represented by their canonical SMILES for molecular modification via the LLM; the embeddings were only used to quantify relationships between molecules before and after modification. The dataset, embedding scheme, and parent selection process are illustrated schematically in Figure .