@inproceedings{saadi-etal-2025-jgu,
    title = "{JGU} Mainz{'}s Submission to the {WMT}25 Shared Task on {LLM}s with Limited Resources for {S}lavic Languages: {MT} and {QA}",
    author = "Saadi, Hossain Shaikh  and
      Bui, Minh Duc  and
      Sanz-Guerrero, Mario  and
      Von Der Wense, Katharina",
    editor = "Haddow, Barry  and
      Kocmi, Tom  and
      Koehn, Philipp  and
      Monz, Christof",
    booktitle = "Proceedings of the Tenth Conference on Machine Translation",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.wmt-1.89/",
    doi = "10.18653/v1/2025.wmt-1.89",
    pages = "1151--1157",
    ISBN = "979-8-89176-341-8",
    abstract = "This paper presents the JGU Mainz submission to the WMT25 Shared Task on LLMs with Limited Resources for Slavic Languages: Machine Translation and Question Answering, focusing on Ukrainian, Upper Sorbian, and Lower Sorbian. For each language, we jointly fine-tune a Qwen2.5-3B-Instruct model for both tasks with parameter-efficient finetuning. Our pipeline integrates additional translation and multiple-choice question answering (QA) data. For Ukrainian QA, we further use retrieval-augmented generation. We also apply ensembling for QA in Upper and Lower Sorbian. Experiments show that our models outperform the baseline on both tasks."
}