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Updated: Jul 9, 2025

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
Published on: December 6, 2024
Even deeper problems with neural network models of language
Thomas G Bever1, Noam Chomsky1, Sandiway Fong1
1Department of Linguistics, University of Arizona, Tucson, AZ, USA tgb@arizona.edu nchomsky3@gmail.com Sandiway@arizona.edu Massimo@arizona.eduhttps://bever.infohttps://chomsky.infohttps://sandiway.arizona.eduhttps://massimo.sbs.arizona.edu.
Abstract:
We recognize today's deep neural network (DNN) models of language behaviors as engineering achievements. However, what we know intuitively and scientifically about language shows that what DNNs are and how they are trained on bare texts, makes them poor models of mind and brain for language organization, as it interacts with infant biology, maturation, experience, unique principles, and natural law.
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