@inproceedings{hus-etal-2025-machine,
    title = "Machine Translation Using Grammar Materials for {LLM} Post-Correction",
    author = "Hus, Jonathan  and
      Anastasopoulos, Antonios  and
      Krasner, Nathaniel",
    editor = "Mager, Manuel  and
      Ebrahimi, Abteen  and
      Pugh, Robert  and
      Rijhwani, Shruti  and
      Von Der Wense, Katharina  and
      Chiruzzo, Luis  and
      Coto-Solano, Rolando  and
      Oncevay, Arturo",
    booktitle = "Proceedings of the Fifth Workshop on NLP for Indigenous Languages of the Americas (AmericasNLP)",
    month = may,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/moar-dois/2025.americasnlp-1.10/",
    doi = "10.18653/v1/2025.americasnlp-1.10",
    pages = "92--99",
    ISBN = "979-8-89176-236-7",
    abstract = "This paper describes George Mason University{'}s submission to the AmericasNLP 2025 Shared Task on Machine Translation into Indigenous Languages. We prompt a large language model (LLM) with grammar reference materials to correct the translations produced by a finetuned Encoder-Decoder machine translation system. This system leads to improvements when translating from the indigenous languages into Spanish indicating that LLMs are capable of using grammar materials to decipher an unseen language."
}