{"ID":2895178,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.09536","arxiv_id":"2507.09536","title":"Adapting Definition Modeling for New Languages: A Case Study on Belarusian","abstract":"Definition modeling, the task of generating new definitions for words in context, holds great prospect as a means to assist the work of lexicographers in documenting a broader variety of lects and languages, yet much remains to be done in order to assess how we can leverage pre-existing models for as-of-yet unsupported languages. In this work, we focus on adapting existing models to Belarusian, for which we propose a novel dataset of 43,150 definitions. Our experiments demonstrate that adapting a definition modeling systems requires minimal amounts of data, but that there currently are gaps in what automatic metrics do capture.","short_abstract":"Definition modeling, the task of generating new definitions for words in context, holds great prospect as a means to assist the work of lexicographers in documenting a broader variety of lects and languages, yet much remains to be done in order to assess how we can leverage pre-existing models for as-of-yet unsupported...","url_abs":"https://arxiv.org/abs/2507.09536","url_pdf":"https://arxiv.org/pdf/2507.09536v1","authors":"[\"Daniela Kazakouskaya\",\"Timothee Mickus\",\"Janine Siewert\"]","published":"2025-07-13T08:35:23Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[]","has_code":false}