3 papers
cs.CL2026
Neural Language Models Learn the Contextual Distributions of Dependency Structures: a statistical learning theory to compositionality
Wang Bojun, Junjie Chen, Holly Jenkins +1
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…
cs.CL2026
Generalization and Memorization along the Learning Trajectory of Neural Language Models: A Geometric Account of Categorization
Wang Bojun, Holly Jenkins, Elizabeth Wonnacott
We investigate how generalization and memorization develop along the learning trajectory of neural language models. Using controlled synthetic grammars, we examine both the geometr…
cs.CL2026
Developmental approach reveals the statistical learning of Neural Language Models: Transformers generalize from the most abstract statistical patterns
Wang Bojun, Holly Jenkins, Elizabeth Wonnacott
In this study, we use a developmental approach to investigate the statistical learning and mental representation of neural language models (NLM). A series of Generative Transformer…