@inproceedings{xiao-etal-2025-toward,
    title = "Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations",
    author = "Xiao, Yimin  and
      Zhang, Yongle  and
      Ki, Dayeon  and
      Bao, Calvin  and
      Martindale, Marianna J.  and
      Vaughn, Charlotte  and
      Gao, Ge  and
      Carpuat, Marine",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-main.1725/",
    pages = "33985--34002",
    ISBN = "979-8-89176-332-6",
    abstract = "As Machine Translation (MT) becomes increasingly commonplace, understanding how the general public perceives and relies on imperfect MT is crucial for contextualizing MT research in real-world applications. We present a human study conducted in a public museum (n=452), investigating how fluency and adequacy errors impact bilingual and non-bilingual users' reliance on MT during casual use. Our findings reveal that non-bilingual users often over-rely on MT due to a lack of evaluation strategies and alternatives, while experiencing the impact of errors can prompt users to reassess future reliance. This highlights the need for MT evaluation and NLP explanation techniques to promote not only MT quality, but also MT literacy among its users."
}