Using a unified graph representation of reactions instead of separate reactant/product graphs enables better learning of chemical transformations, leading to more accurate yield predictions and a foundation model that could generalize across diverse reaction types.
RxnCLF is a self-supervised learning framework that represents chemical reactions as unified graphs (condensed reaction graphs) to better capture how molecules transform.