@inproceedings{tedeschi-etal-2022-id10m,
    title = "{ID}10{M}: Idiom Identification in 10 Languages",
    author = "Tedeschi, Simone  and
      Martelli, Federico  and
      Navigli, Roberto",
    editor = "Carpuat, Marine  and
      de Marneffe, Marie-Catherine  and
      Meza Ruiz, Ivan Vladimir",
    booktitle = "Findings of the Association for Computational Linguistics: NAACL 2022",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.findings-naacl.208/",
    doi = "10.18653/v1/2022.findings-naacl.208",
    pages = "2715--2726",
    abstract = "Idioms are phrases which present a figurative meaning that cannot be (completely) derived by looking at the meaning of their individual components. Identifying and understanding idioms in context is a crucial goal and a key challenge in a wide range of Natural Language Understanding tasks. Although efforts have been undertaken in this direction, the automatic identification and understanding of idioms is still a largely under-investigated area, especially when operating in a multilingual scenario. In this paper, we address such limitations and put forward several new contributions: we propose a novel multilingual Transformer-based system for the identification of idioms; we produce a high-quality automatically-created training dataset in 10 languages, along with a novel manually-curated evaluation benchmark; finally, we carry out a thorough performance analysis and release our evaluation suite at \url{https://github.com/Babelscape/ID10M}."
}