@inproceedings{ramponi-etal-2025-arg2st,
    title = "{ARG}2{ST} at {CQ}s-Gen 2025: Critical Questions Generation through {LLM}s and Usefulness-based Selection",
    author = "Ramponi, Alan  and
      Genoni, Gaudenzia  and
      Tonelli, Sara",
    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/acl25-workshop-ingestion/2025.argmining-1.29/",
    pages = "301--313",
    ISBN = "979-8-89176-258-9",
    abstract = "Critical questions (CQs) generation for argumentative texts is a key task to promote critical thinking and counter misinformation. In this paper, we present a two-step approach for CQs generation that i) uses a large language model (LLM) for generating candidate CQs, and ii) leverages a fine-tuned classifier for ranking and selecting the top-k most useful CQs to present to the user. We show that such usefulness-based CQs selection consistently improves the performance over the standard application of LLMs. Our system was designed in the context of a shared task on CQs generation hosted at the 12th Workshop on Argument Mining, and represents a viable approach to encourage future developments on CQs generation. Our code is made available to the research community."
}