@inproceedings{qian-2024-automating,
    title = "Automating Idiom Translation with Cross-Lingual Natural Language Generation Grounded In Semantic Analyses Using Large Language Models",
    author = "Qian, Ming",
    editor = "Martindale, Marianna  and
      Campbell, Janice  and
      Savenkov, Konstantin  and
      Goel, Shivali",
    booktitle = "Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 2: Presentations)",
    month = sep,
    year = "2024",
    address = "Chicago, USA",
    publisher = "Association for Machine Translation in the Americas",
    url = "https://preview.aclanthology.org/ingest-emnlp/2024.amta-presentations.7/",
    pages = "95--115",
    abstract = "Idioms exhibit varying degrees of semantic transparency, making their translation challenging. Cross-language differences in idiom usage and connotations add complexity. Using a large language modeling (LLM) approach, we automate Chinese-to-English idiom translation in three steps: (1) Semantic analysis of Chinese idioms using ontology or FrameNet to identify key concepts/relationships like action, purpose, outcome, and context. (2) Generation of multi-word English expressions reflecting these concepts. (3) Selection of the top English idiom candidate that closely matches the Chinese idiom{'}s meaning. Applied to examples like `破釜沉舟', `刀山火海', and `抛砖引玉', our method performs on par with human experts. The semantic reasoning approach enhances transparency in LLM decisions, simulating logical inferences over the semantic framework."
}