@inproceedings{choudhary-oriordan-2023-multilingual,
    title = "Multilingual End-to-end Dependency Parsing with Linguistic Typology knowledge",
    author = "Choudhary, Chinmay  and
      O{'}riordan, Colm",
    editor = "Beinborn, Lisa  and
      Goswami, Koustava  and
      Murado{\u{g}}lu, Saliha  and
      Sorokin, Alexey  and
      Kumar, Ritesh  and
      Shcherbakov, Andreas  and
      Ponti, Edoardo M.  and
      Cotterell, Ryan  and
      Vylomova, Ekaterina",
    booktitle = "Proceedings of the 5th Workshop on Research in Computational Linguistic Typology and Multilingual NLP",
    month = may,
    year = "2023",
    address = "Dubrovnik, Croatia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.sigtyp-1.2",
    doi = "10.18653/v1/2023.sigtyp-1.2",
    pages = "12--21",
    abstract = "We evaluate a Multilingual End-to-end BERT based Dependency Parser which parses an input sentence by directly predicting the relative head-position for each word within it. Our model is a Cross-lingual dependency parser which is trained on a diverse polyglot corpus of high-resource source languages, and is applied on a low-resource target language. To make model more robust to typological variations between source and target languages, and to facilitate the cross-lingual transferring, we utilized the Linguistic typology knowledge, available in typological databases WALS and URIEL. We induce such typology knowledge within our model through an auxiliary task within Multi-task Learning framework.",
}