@inproceedings{zasina-2025-automatic,
    title = "Automatic Generation of Corpus-Based Exercises Using Generative {AI}",
    author = "Zasina, Adrian Jan",
    editor = "Chang, Kai-Wei  and
      Lu, Ke-Han  and
      Yang, Chih-Kai  and
      Tam, Zhi-Rui  and
      Chang, Wen-Yu  and
      Wang, Chung-Che",
    booktitle = "Proceedings of the 37th Conference on Computational Linguistics and Speech Processing (ROCLING 2025)",
    month = nov,
    year = "2025",
    address = "National Taiwan University, Taipei City, Taiwan",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.rocling-main.9/",
    pages = "80--86",
    ISBN = "979-8-89176-379-1",
    abstract = "This study explores the automatic generation of corpus-based language exercises using generative AI models. We focus on the interaction between language models and corpus data, detailing a workflow in which lexical and syntactic patterns are extracted from a tagged corpus and structured prompts are constructed to guide the model in producing sentence-level exercises. The generated exercises reveal both the potential of AI-driven approaches. However, observations highlight the necessity of careful design and critical evaluation when integrating generative models with corpus-based language materials. By analysing these processes from a computational linguistics perspective, this study contributes to understanding how generative AI can interact with structured linguistic data, informing future applications in automated language resources."
}