If a model supports memory mechanisms, subsequent predictions will also be based on the previous ones. Thus, SMILESRNN will pass the currently predicted token back to the model to predict the next one (teacher forcing, Figure ). Another important remark is that having received a SMILES fragment instead of {, the model successively updates its memory without making predictions (warm-up period), then proceeds generating the remaining fragment.