@inproceedings{nieminen-2024-adding,
    title = "Adding soft terminology constraints to pre-trained generic {MT} models by means of continued training",
    author = "Nieminen, Tommi",
    editor = "Tezcan, Arda  and
      S{\'a}nchez-Cartagena, V{\'i}ctor M.  and
      Espl{\`a}-Gomis, Miquel",
    booktitle = "Proceedings of the First International Workshop on Knowledge-Enhanced Machine Translation",
    month = jun,
    year = "2024",
    address = "Sheffield, United Kingdom",
    publisher = "European Association for Machine Translation (EAMT)",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.kemt-1.3/",
    pages = "21--33",
    abstract = "This article describes an efficient method of adding terminology support to existing machine translation models. The training of the pre-trained models is continued with parallel data where strings identified as terms in the source language data have been annotated with the lemmas of the corresponding target terms. Evaluation using standard test sets and methods confirms that continued training from generic base models can produce term models that are competitive with models specifically trained as term models."
}