Model Evaluation -For evaluation, the validation set of molecules was used in two different ways. First, it served as a set of pairs of molecules to compute information-theory-based scores of ML models. In this work, we report and discuss perplexity of ML models, as shown in Figs. and, as a representative score from this group; no new conclusions were found from other information-theory-based scores (data not shown). Perplexity ppl is defined, as usual, as: 𝑝𝑝𝑙 = exp (𝐿/𝑁), where L is the loss function minimized to train the model, and N is the number of "words" (output molecules in our case). We used the default choice of the loss function in OpenNMT.