@inproceedings{karan-etal-2020-classification,
    title = "Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction",
    author = "Karan, Vanja Mladen  and
      Vuli{\'c}, Ivan  and
      Korhonen, Anna  and
      Glava{\v{s}}, Goran",
    editor = "Jurafsky, Dan  and
      Chai, Joyce  and
      Schluter, Natalie  and
      Tetreault, Joel",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.acl-main.618/",
    doi = "10.18653/v1/2020.acl-main.618",
    pages = "6915--6922",
    abstract = "Effective projection-based cross-lingual word embedding (CLWE) induction critically relies on the iterative self-learning procedure. It gradually expands the initial small seed dictionary to learn improved cross-lingual mappings. In this work, we present ClassyMap, a classification-based approach to self-learning, yielding a more robust and a more effective induction of projection-based CLWEs. Unlike prior self-learning methods, our approach allows for integration of diverse features into the iterative process. We show the benefits of ClassyMap for bilingual lexicon induction: we report consistent improvements in a weakly supervised setup (500 seed translation pairs) on a benchmark with 28 language pairs."
}