Neural Language Models Learn the Contextual Distributions of Dependency Structures: a statistical learning theory to compositionality

It is unclear how Neural Language Models (NLMs) acquire the structural meaning encoded by grammatical structures that is independent of lexical semantics. We propose a statistical learning process in which learned dependency structures themselves become new distributional units for subsequent statis