Transformers on synthetic grammar acquire abstract global statistical knowledge first, then local dependencies, showing initial over-generalizations that are later constrained.
(2025).An investigation of comparative correlative constructions in auto-regressive large language models: From construction grammar to computational understanding[Preprint]
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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.