@inproceedings{jon-etal-2025-cuni,
    title = "{CUNI} at {WMT}25 General Translation Task",
    author = "Jon, Josef  and
      Hrabal, Miroslav  and
      Popel, Martin  and
      Bojar, Ond{\v{r}}ej",
    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/ingest-emnlp/2025.wmt-1.44/",
    pages = "680--687",
    ISBN = "979-8-89176-341-8",
    abstract = "This paper describes the CUNI submissions to the WMT25 General Translation task, namely for the English to Czech, English to Serbian, Czech to German and Czech to Ukrainian language pairs. We worked in multiple teams, each with a different approach, spanning from traditional, smaller Transformer NMT models trained on both sentence and document level, to fine-tuning LLMs using LoRA and CPO. We show that these methods are effective in improving automatic MT evaluation scores compared to the base pretrained models."
}