The SMILES corrector had a lower performance when applied to invalid SMILES from the generative models exemplified by the percentage of valid outputs ranging from 35 to 80 %, with the errors from the GAN being the easiest to correct (Figure ). This validity rate range is similar to the results reported by Zheng et al., in the related task of correcting invalid SMILES grammar in reactants .