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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Not-so-strange love: Language models and generative linguistic theories are more compatible than they appear
1Yale University, USA tom.mccoy@yale.edu.
The Behavioral and Brain Sciences
|June 30, 2026
Abstract
None:
Futrell and Mahowald frame the success of neural language models (LMs) as supporting gradient, usage-based linguistic theories. I argue that LMs can also instantiate theories based on formal structures - the types of theories seen in the generative tradition. This argument expands the space of theories that can be tested with LMs, potentially enabling reconciliations between usage-based and generative accounts.
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