COMPUTATIONAL LINGUISTICS STUDIES

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Challenge:	Hierarchical Multiscale LSTM model learns structure from character input . high complexity of architecture, training and implementations might hinder its applicability .
Approach:	They propose to reproduce and ablate hierarchical multiscale LSTM language model and show that simplifying certain aspects of the architecture can improve its performance.
Outcome:	The proposed model performs better when simplified and linguistic units are learned by different levels of the model.

Papers with computational linguistics studies