@inproceedings{arnett-etal-2025-acquisition,
    title = "On the Acquisition of Shared Grammatical Representations in Bilingual Language Models",
    author = "Arnett, Catherine  and
      Chang, Tyler A.  and
      Michaelov, James A.  and
      Bergen, Ben",
    editor = "Che, Wanxiang  and
      Nabende, Joyce  and
      Shutova, Ekaterina  and
      Pilehvar, Mohammad Taher",
    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingestion-acl-25/2025.acl-long.1010/",
    pages = "20707--20726",
    ISBN = "979-8-89176-251-0",
    abstract = "Crosslingual transfer is crucial to contemporary language models' multilingual capabilities, but how it occurs is not well understood. Weask what happens to a monolingual language model when it begins to be trained on a second language. Specifically, we train small bilingual models for which we control the amount of data for each language and the order of language exposure. To find evidence of shared multilingual representations, we turn to structural priming, a method used to study grammatical representations in humans. We first replicate previous crosslingual structural priming results and find that after controlling for training data quantity and language exposure, there are asymmetrical effects across language pairs and directions. We argue that this asymmetry may shape hypotheses about human structural priming effects. We also find that structural priming effects are less robust for less similar language pairs, highlighting potential limitations of crosslingual transfer learning and shared representations for typologically diverse languages."
}