@inproceedings{francis-etal-2024-gattina,
    title = "{GATTINA} - {G}ener{A}tion of {T}i{T}les for {I}talian News Articles: A {CALAMITA} Challenge",
    author = "Francis, Maria  and
      Rinaldi, Matteo  and
      Gili, Jacopo  and
      De Cosmo, Leonardo  and
      Iannaccone, Sandro  and
      Nissim, Malvina  and
      Patti, Viviana",
    editor = "Dell'Orletta, Felice  and
      Lenci, Alessandro  and
      Montemagni, Simonetta  and
      Sprugnoli, Rachele",
    booktitle = "Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)",
    month = dec,
    year = "2024",
    address = "Pisa, Italy",
    publisher = "CEUR Workshop Proceedings",
    url = "https://preview.aclanthology.org/Ingest-2025-COMPUTEL/2024.clicit-1.121/",
    pages = "1094--1105",
    ISBN = "979-12-210-7060-6",
    abstract = "We introduce a new benchmark designed to evaluate the ability of Large Language Models (LLMs) to generate Italian-language headlines for science news articles. The benchmark is based on a large dataset of science news articles obtained from Ansa Scienza and Galileo, two important Italian media outlets. Effective headline generation requires more than summarizing article content; headlines must also be informative, engaging, and suitable for the topic and target audience, making automatic evaluation particularly challenging. To address this, we propose two novel transformer-based metrics to assess headline quality. We aim for this benchmark to support the evaluation of Italian LLMs and to foster the development of tools to assist in editorial workflows."
}