@inproceedings{calvo-figueras-etal-2025-overview,
    title = "Overview of the Critical Questions Generation Shared Task",
    author = "Calvo Figueras, Blanca  and
      Agerri, Rodrigo  and
      Heredia, Maite  and
      Bengoetxea, Jaione  and
      Cabrio, Elena  and
      Villata, Serena",
    editor = "Chistova, Elena  and
      Cimiano, Philipp  and
      Haddadan, Shohreh  and
      Lapesa, Gabriella  and
      Ruiz-Dolz, Ramon",
    booktitle = "Proceedings of the 12th Argument mining Workshop",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/mtsummit-25-ingestion/2025.argmining-1.23/",
    doi = "10.18653/v1/2025.argmining-1.23",
    pages = "243--257",
    ISBN = "979-8-89176-258-9",
    abstract = "The proliferation of AI technologies has reinforced the importance of developing critical thinking skills. We propose leveraging Large Language Models (LLMs) to facilitate the generation of critical questions: inquiries designed to identify fallacious or inadequately constructed arguments. This paper presents an overview of the first shared task on Critical Questions Generation (CQs-Gen). Thirteen teams investigated various methodologies for generating questions that critically assess arguments within the provided texts. The highest accuracy achieved was 67.6, indicating substantial room for improvement in this task. Moreover, three of the four top-performing teams incorporated argumentation scheme annotations to enhance their systems. Finally, while most participants employed open-weight models, the two highest-ranking teams relied on proprietary LLMs."
}