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Generative Linguistics and Neural Networks at 60: Foundation, Friction, and Fusion

Published online by Cambridge University Press:  01 January 2026

Joe Pater
Joe Pater*
Affiliation:
University of Massachusetts Amherst
*
[pater@linguist.umass.edu]
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Abstract

The birthdate of both generative linguistics and neural networks can be taken as 1957, the year of the publication of foundational work by both Noam Chomsky and Frank Rosenblatt. This article traces the development of these two approaches to cognitive science, from their largely autonomous early development in the first thirty years, through their collision in the 1980s around the past-tense debate (Rumelhart & McClelland 1986, Pinker & Prince 1988) and their integration in much subsequent work up to the present. Although this integration has produced a considerable body of results, the continued general gulf between these two lines of research is likely impeding progress in both: on learning in generative linguistics, and on the representation of language in neural modeling. The article concludes with a brief argument that generative linguistics is unlikely to fulfill its promise of accounting for language learning if it continues to maintain its distance from neural and statistical approaches to learning.

Keywords

generative linguisticsdeep learningconnectionismneural networkscomputational linguisticssyntaxphonologyNoam ChomskyFrank Rosenblatt

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Type
Perspectives
Information
Language , Volume 95 , Issue 1 , March 2019 , pp. e41 - e74
Copyright
Copyright © 2019 Linguistic Society of America

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