{"ID":3006052,"CreatedAt":"2026-06-03T03:09:48.883664427Z","UpdatedAt":"2026-06-04T19:14:31.964469513Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.02806","arxiv_id":"2606.02806","title":"Translating Classical Poetry into Modern Prose","abstract":"We introduce Padyam2Gadyam, a dataset for the task of poem-to-prose translation from 13th-17th Century Telugu Classical Poetry to contemporary Telugu and English prose. The dataset consists of 600 poems and their human-verified Telugu and English prose translations. We evaluated 5 contemporary Large Language Models (LLMs) on their ability to do poem-to-prose translation into Telugu and English. Our results indicate that while there are differences across LLMs, their overall performance leave a large room for improvement in both languages. Through qualitative analysis, we discuss the the capabilities and limitations of contemporary MT evaluation approaches for this task.","short_abstract":"We introduce Padyam2Gadyam, a dataset for the task of poem-to-prose translation from 13th-17th Century Telugu Classical Poetry to contemporary Telugu and English prose. The dataset consists of 600 poems and their human-verified Telugu and English prose translations. We evaluated 5 contemporary Large Language Models (LL...","url_abs":"https://arxiv.org/abs/2606.02806","url_pdf":"https://arxiv.org/pdf/2606.02806v1","authors":"[\"Chalamalasetti Kranti\",\"Sowmya Vajjala\"]","published":"2026-06-01T19:24:50Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}