@inproceedings{castaldo-monti-2024-prompting,
    title = "Prompting Large Language Models for Idiomatic Translation",
    author = "Castaldo, Antonio  and
      Monti, Johanna",
    editor = "Vanroy, Bram  and
      Lefer, Marie-Aude  and
      Macken, Lieve  and
      Ruffo, Paola",
    booktitle = "Proceedings of the 1st Workshop on Creative-text Translation and Technology",
    month = jun,
    year = "2024",
    address = "Sheffield, United Kingdom",
    publisher = "European Association for Machine Translation",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.ctt-1.4/",
    pages = "32--39",
    abstract = "Large Language Models (LLMs) have demonstrated impressive performance in translating content across different languages and genres. Yet, their potential in the creative aspects of machine translation has not been fully explored. In this paper, we seek to identify the strengths and weaknesses inherent in different LLMs when applied to one of the most prominent features of creative works: the translation of idiomatic expressions. We present an overview of their performance in the EN$\rightarrow$IT language pair, a context characterized by an evident lack of bilingual data tailored for idiomatic translation. Lastly, we investigate the impact of prompt design on the quality of machine translation, drawing on recent findings which indicate a substantial variation in the performance of LLMs depending on the prompts utilized."
}