Colorless Green Recurrent Networks Dream Hierarchically

@inproceedings{Gulordava2018ColorlessGR,
  title={Colorless Green Recurrent Networks Dream Hierarchically},
  author={Kristina Gulordava and Piotr Bojanowski and Edouard Grave and Tal Linzen and Marco Baroni},
  booktitle={NAACL-HLT},
  year={2018}
}

• Kristina Gulordava, Piotr Bojanowski, +2 authors Marco Baroni
• Published in NAACL-HLT 2018
• DOI:10.18653/v1/N18-1108

Recurrent neural networks (RNNs) have achieved impressive results in a variety of linguistic processing tasks, suggesting that they can induce non-trivial properties of language. We investigate here to what extent RNNs learn to track abstract hierarchical syntactic structure. We test whether RNNs trained with a generic language modeling objective in four languages (Italian, English, Hebrew, Russian) can predict long-distance number agreement in various constructions. We include in our… CONTINUE READING

View PDF on ArXiv

Save to Library

Create Alert

Cite