Neural Language Models Learn the Contextual Distributions of Dependency Structures: a statistical learning theory to compositionality
It is argued that this process provides a statistical-learning account of how NLMs solve the compositionality problem in language, and the possibility that this statistical learning process provides an explanatory theory on how language cognition could emerge from pure distributional statistics.
Bo-Juan Wang, Chen Jun Jie, Holly E. Jenkins et al.
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