Statistical grammar induction shows the GROWING (bottom-up) maturational account of syntactic category acquisition significantly outperforms the INWARD account across three metrics under identical input and learning conditions.
Constructing a Language: A Usage-Based Theory of Language Acquisition , ISBN =
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Transformers on synthetic grammar acquire abstract global statistical knowledge first, then local dependencies, showing initial over-generalizations that are later constrained.
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A Computational Operationalisation of Competing Maturational Theories of Syntactic Development via Statistical Grammar Induction
Statistical grammar induction shows the GROWING (bottom-up) maturational account of syntactic category acquisition significantly outperforms the INWARD account across three metrics under identical input and learning conditions.
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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.