Recent studies have explored the use of sequence-based neural networks for translating between chemical representations, such as SMILES strings and IUPAC names . These studies highlight the potential of machine learning to address the challenges associated with IUPAC name generation, paving the way for more accessible and efficient tools for chemists. However, we have no intention of competing with commercial rule-based tools that are more reliable due to their deterministic nature.