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Bo-Juan Wang

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#natural language process... Preprint Sep 2026

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. · 0 citations
#natural language process... Preprint Sep 2026

Generalization and Memorization along the Learning Trajectory of Neural Language Models: A Geometric Account of Categorization

This work finds that continuous regions of representation space not occupied by observed tokens become systematically structured from the earliest stages of learning, forming category-level geometric organization that supports generalization to unattested combinations.

Bo-Juan Wang, Holly E. Jenkins, E. Wonnacott · 0 citations

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