@inproceedings{pirinen-wiechetek-2025-exploring,
    title = "Exploring Limitations and Risks of {LLM}-Based Grammatical Error Correction for Indigenous Languages",
    author = "Pirinen, Flammie A  and
      Wiechetek, Linda",
    editor = "Lachler, Jordan  and
      Agyapong, Godfred  and
      Arppe, Antti  and
      Moeller, Sarah  and
      Chaudhary, Aditi  and
      Rijhwani, Shruti  and
      Rosenblum, Daisy",
    booktitle = "Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages",
    month = mar,
    year = "2025",
    address = "Honolulu, Hawaii, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Ingest-2025-COMPUTEL/2025.computel-main.8/",
    pages = "74--81",
    ISBN = "None",
    abstract = "Rule-based grammatical error correction has long been seen as the most effective way to create user-friendly end-user systems for gram- matical error correction (GEC). However, in the recent years the large language models and generative AI systems based on that technol- ogy have been progressed fast to challenge the traditional GEC approach. In this article we show which possibilities and limitations this approach bears for Indigenous languages that have more limited digital presence in the large language model data and a different literacy background than English. We show experi- ments in North S{\'a}mi, an Indigenous language of Northern Europe."
}