Local sequence alignment can be used to detect structural similarities in poems and trace variations in poetic meters across languages and time periods.
Despite carefully configured neural networks achieving high accuracy in classifying the authorship of classical Latin verse, the reasoning behind their decisions remains inscrutable, failing to provide meaningful insights into poetic style.