MolSC: Leveraging Substituent Contributions to Enhance Fine-grained Molecular Understanding in LLMs

Recent advances in natural language processing have led to molecular Large Language Models (LLMs) with strong performance across diverse chemistry tasks. However, they still struggle to capture fine-grained structure-property relationships, particularly how small, localized modifications alter a mol