@article{choenni-etal-2023-cross,
    title = "Cross-Lingual Transfer with Language-Specific Subnetworks for Low-Resource Dependency Parsing",
    author = "Choenni, Rochelle  and
      Garrette, Dan  and
      Shutova, Ekaterina",
    journal = "Computational Linguistics",
    month = sep,
    year = "2023",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://aclanthology.org/2023.cl-3.3",
    doi = "10.1162/coli_a_00482",
    pages = "613--641",
    abstract = "Large multilingual language models typically share their parameters across all languages, which enables cross-lingual task transfer, but learning can also be hindered when training updates from different languages are in conflict. In this article, we propose novel methods for using language-specific subnetworks, which control cross-lingual parameter sharing, to reduce conflicts and increase positive transfer during fine-tuning. We introduce dynamic subnetworks, which are jointly updated with the model, and we combine our methods with meta-learning, an established, but complementary, technique for improving cross-lingual transfer. Finally, we provide extensive analyses of how each of our methods affects the models.",
}