What Do Recurrent Neural Network Grammars Learn About Syntax?

@inproceedings{Smith2017WhatDR,
  title={What Do Recurrent Neural Network Grammars Learn About Syntax?},
  author={Noah A. Smith and Chris Dyer and Miguel Ballesteros and Graham Neubig and Lingpeng Kong and Adhiguna Kuncoro},
  booktitle={EACL},
  year={2017}
}
Recurrent neural network grammars (RNNG) are a recently proposed probabilistic generative modeling family for natural language. They show state-ofthe-art language modeling and parsing performance. We investigate what information they learn, from a linguistic perspective, through various ablations to the model and the data, and by augmenting the model with an attention mechanism (GA-RNNG) to enable closer inspection. We find that explicit modeling of composition is crucial for achieving the best… CONTINUE READING

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