Many data-driven applications therefore attempt to ignore the fact that many or most reactions are unbalanced and operate directly on such imperfect reaction data. This is in particular the case of atom-atom mapping methods. RXNMapper and GraphormerMapper apply machine learning for reaction mapping and atom embedding improvements, respectively, without directly addressing reaction imbalances.