@inproceedings{ruder-etal-2019-unsupervised,
    title = "Unsupervised Cross-Lingual Representation Learning",
    author = "Ruder, Sebastian  and
      S{\o}gaard, Anders  and
      Vuli{\'c}, Ivan",
    editor = "Nakov, Preslav  and
      Palmer, Alexis",
    booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts",
    month = jul,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/P19-4007/",
    doi = "10.18653/v1/P19-4007",
    pages = "31--38",
    abstract = "In this tutorial, we provide a comprehensive survey of the exciting recent work on cutting-edge weakly-supervised and unsupervised cross-lingual word representations. After providing a brief history of supervised cross-lingual word representations, we focus on: 1) how to induce weakly-supervised and unsupervised cross-lingual word representations in truly resource-poor settings where bilingual supervision cannot be guaranteed; 2) critical examinations of different training conditions and requirements under which unsupervised algorithms can and cannot work effectively; 3) more robust methods for distant language pairs that can mitigate instability issues and low performance for distant language pairs; 4) how to comprehensively evaluate such representations; and 5) diverse applications that benefit from cross-lingual word representations (e.g., MT, dialogue, cross-lingual sequence labeling and structured prediction applications, cross-lingual IR)."
}