@inproceedings{romney-robinson-etal-2025-jhu,
    title = "{JHU} {IWSLT} 2025 Low-resource System Description",
    author = "Romney Robinson, Nathaniel  and
      Bafna, Niyati  and
      He, Xiluo  and
      Lupicki, Tom  and
      Shankar, Lavanya  and
      Xiao, Cihan  and
      Sun, Qi  and
      Murray, Kenton  and
      Yarowsky, David",
    editor = "Salesky, Elizabeth  and
      Federico, Marcello  and
      Anastasopoulos, Antonis",
    booktitle = "Proceedings of the 22nd International Conference on Spoken Language Translation (IWSLT 2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria (in-person and online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/acl25-workshop-ingestion/2025.iwslt-1.32/",
    pages = "315--323",
    ISBN = "979-8-89176-272-5",
    abstract = "We present the Johns Hopkins University{'}s submission to the 2025 IWSLT Low-Resource Task. We competed on all 10 language pairs. Our approach centers around ensembling methods {--} specifically Minimum Bayes Risk Decoding. We find that such ensembling often improves performance only slightly over the best performing stand-alone model, and that in some cases it can even hurt performance slightly."
}