RxnNano:Training Compact LLMs for Chemical Reaction and Retrosynthesis Prediction via Hierarchical Curriculum Learning

Researchers developed RxnNano, a compact 0.5B-parameter AI model for chemical reaction prediction that outperforms much larger 7B+ parameter models by 23.5% through novel training techniques focused on chemical understanding rather than scale. The framework uses hierarchical curriculum learning and chemical consistency objectives to improve drug discovery and synthesis planning applications.