Grammar Induction with Neural Language Models: An Unusual Replication

WS 2018 Phu Mon HtutKyunghyun ChoSamuel R. Bowman

A substantial thread of recent work on latent tree learning has attempted to develop neural network models with parse-valued latent variables and train them on non-parsing tasks, in the hope of having them discover interpretable tree structure. In a recent paper, Shen et al. (2018) introduce such a model and report near-state-of-the-art results on the target task of language modeling, and the first strong latent tree learning result on constituency parsing... (read more)

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