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Ionut Constantinescu
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Publisher: Journals Gateway
Transactions of the Association for Computational Linguistics (2025) 13: 96–120.
Published: 24 January 2025
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Abstract
View articletitled, Investigating Critical Period Effects in Language Acquisition through Neural Language Models
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for article titled, Investigating Critical Period Effects in Language Acquisition through Neural Language Models
Humans appear to have a critical period (CP) for language acquisition: Second language (L 2 ) acquisition becomes harder after early childhood, and ceasing exposure to a first language (L 1 ) after this period (but not before) typically does not lead to substantial loss of L 1 proficiency. It is unknown whether these CP effects result from innately determined brain maturation or as a stabilization of neural connections naturally induced by experience. In this study, we use language models (LMs) to test the extent to which these phenomena are peculiar to humans, or shared by a broader class of language learners. We vary the age of exposure by training LMs on language pairs in various experimental conditions, and find that LMs, which lack any direct analog to innate maturational stages, do not show CP effects when the age of exposure of L 2 is delayed. Our results contradict the claim that CP effects are an inevitable result of statistical learning, and they are consistent with an innate mechanism for CP effects. We show that we can reverse-engineer the CP by introducing a regularizer partway through training to simulate a maturational decrease in plasticity. All in all, our results suggest that L 1 learning on its own may not be enough to induce a CP, and additional engineering is necessary to make language models more cognitively plausible.