@inproceedings{gonen-etal-2022-analyzing,
    title = "Analyzing Gender Representation in Multilingual Models",
    author = "Gonen, Hila  and
      Ravfogel, Shauli  and
      Goldberg, Yoav",
    editor = "Gella, Spandana  and
      He, He  and
      Majumder, Bodhisattwa Prasad  and
      Can, Burcu  and
      Giunchiglia, Eleonora  and
      Cahyawijaya, Samuel  and
      Min, Sewon  and
      Mozes, Maximilian  and
      Li, Xiang Lorraine  and
      Augenstein, Isabelle  and
      Rogers, Anna  and
      Cho, Kyunghyun  and
      Grefenstette, Edward  and
      Rimell, Laura  and
      Dyer, Chris",
    booktitle = "Proceedings of the 7th Workshop on Representation Learning for NLP",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2022.repl4nlp-1.8/",
    doi = "10.18653/v1/2022.repl4nlp-1.8",
    pages = "67--77",
    abstract = "Multilingual language models were shown to allow for nontrivial transfer across scripts and languages. In this work, we study the structure of the internal representations that enable this transfer. We focus on the representations of gender distinctions as a practical case study, and examine the extent to which the gender concept is encoded in shared subspaces across different languages. Our analysis shows that gender representations consist of several prominent components that are shared across languages, alongside language-specific components. The existence of language-independent and language-specific components provides an explanation for an intriguing empirical observation we make'':'' while gender classification transfers well across languages, interventions for gender removal trained on a single language do not transfer easily to others."
}