Designing a large language model for chemists - Xiaoyi Chen; Haixu Tang (Patterns)
In a recent issue of Cell Reports Physical Science, Zhao et al. introduced ChemDFM, a foundational large language model designed specifically for chemistry. The model bridges the gap between general-purpose language models and specialized chemical knowledge, including the integration of multimodal capabilities for spectroscopic data interpretation, improved numerical reasoning, and connectivity with chemical tools and databases to enhance practical research applications. This approach demonstrates how domain adaptation can transform AI tools into collaborative research partners for scientific discovery.