@inproceedings{nikolova-stoupak-etal-2024-llm,
    title = "{LLM}-Generated Contexts to Practice Specialised Vocabulary: Corpus Presentation and Comparison",
    author = "Nikolova-Stoupak, Iglika  and
      Bibauw, Serge  and
      Dumont, Amandine  and
      Stas, Fran{\c{c}}oise  and
      Watrin, Patrick  and
      Fran{\c{c}}ois, Thomas",
    editor = "Balaguer, Mathieu  and
      Bendahman, Nihed  and
      Ho-dac, Lydia-Mai  and
      Mauclair, Julie  and
      G Moreno, Jose  and
      Pinquier, Julien",
    booktitle = "Actes de la 31{\`e}me Conf{\'e}rence sur le Traitement Automatique des Langues Naturelles, volume 1 : articles longs et prises de position",
    month = "7",
    year = "2024",
    address = "Toulouse, France",
    publisher = "ATALA and AFPC",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.jeptalnrecital-taln.33/",
    pages = "472--498",
    abstract = "This project evaluates the potential of LLM and dynamic corpora to generate contexts ai- med at the practice and acquisition of specialised English vocabulary. We compared reference contexts{---}handpicked by expert teachers{---}for a specialised vocabulary list to contexts generated by three recent large language models (LLM) of different sizes (Mistral-7B-Instruct, Vicuna-13B, and Gemini 1.0 Pro) and to contexts extracted from articles web-crawled from specialised websites. The comparison uses a representative set of length-based, morphosyntactic, semantic, and discourse- related textual characteristics. We conclude that the LLM-based corpora can be combined effectively with a web-crawled one to form an academic corpus characterised by appropriate complexity and textual variety."
}