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Crosslingual Structural Priming and the Pre-Training Dynamics of Bilingual Language Models

arXiv 2310.07929 ↗First posted 11 Oct 2023cs.CLcited by 0

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Abstract (arXiv)

Do multilingual language models share abstract grammatical representations across languages, and if so, when do these develop? Following Sinclair et al. (2022), we use structural priming to test for abstract grammatical representations with causal effects on model outputs. We extend the approach to a Dutch-English bilingual setting, and we evaluate a Dutch-English language model during pre-training. We find that crosslingual structural priming effects emerge early after exposure to the second language, with less than 1M tokens of data in that language. We discuss implications for data contamination, low-resource transfer, and how abstract grammatical representations emerge in multilingual models.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 20 references that are in the map. First posted on arXiv 11 Oct 2023.

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9 of 20 references.

References · 9

  1. 2020XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalizationcited by 742
  2. 2019On the Cross-lingual Transferability of Monolingual Representationscited by 578
  3. 2019Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERTcited by 301
  4. 2021Language Models are Few-shot Multilingual Learnerscited by 92
  5. 2022Language Contamination Helps Explain the Cross-lingual Capabilities of English Pretrained Modelscited by 92
  6. 2019Cross-Lingual Natural Language Generation via Pre-Trainingcited by 63
  7. 2021Structural Persistence in Language Models: Priming as a Window into Abstract Language Representationscited by 44
  8. 2019Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Modelscited by 29
  9. 2022Neural reality of argument structure constructionscited by 25

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