Large Language Models as Proxies for Theories of Human Linguistic Cognition

Imry Ziv, Nur Lan, Emmanuel Chemla, Roni Katzir
2/11/2025
cs.CL

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Abstract

We consider the possible role of current large language models (LLMs) in the study of human linguistic cognition. We focus on the use of such models as proxies for theories of cognition that are relatively linguistically-neutral in their representations and learning but differ from current LLMs in key ways. We illustrate this potential use of LLMs as proxies for theories of cognition in the context of two kinds of questions: (a) whether the target theory accounts for the acquisition of a given pattern from a given corpus; and (b) whether the target theory makes a given typologically-attested pattern easier to acquire than another, typologically-unattested pattern. For each of the two questions we show, building on recent literature, how current LLMs can potentially be of help, but we note that at present this help is quite limited.

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@article{ziv2025large,
  title  = {Large Language Models as Proxies for Theories of Human Linguistic Cognition},
  author = {Imry Ziv and Nur Lan and Emmanuel Chemla and Roni Katzir},
  year   = {2025},
  eprint = {2502.07687},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.07687v2}
}

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