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Rich data drive generalization: Lessons from machine learning for linguistics and cognitive science
1Google DeepMind, USA lampinen@google.com.
The Behavioral and Brain Sciences
|June 30, 2026
Abstract
None:
The diversity of variation captured in data can strongly affect the generalization of a learning system - even when that variation occurs along axes orthogonal to the generalization in question. Thus, I argue that data richness both distinguishes current language models from prior linguistic models and may still underlie their remaining linguistic data inefficiency.
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