Transformers on synthetic grammar acquire abstract global statistical knowledge first, then local dependencies, showing initial over-generalizations that are later constrained.
(2015).Argument Structure in Usage-Based Construction Grammar: Experimental and corpus-based perspectives(Vol
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Developmental approach reveals the statistical learning of Neural Language Models: Transformers generalize from the most abstract statistical patterns
Transformers on synthetic grammar acquire abstract global statistical knowledge first, then local dependencies, showing initial over-generalizations that are later constrained.