Stack-propagation: Improved Representation Learning for Syntax

@article{Zhang2016StackpropagationIR,
  title={Stack-propagation: Improved Representation Learning for Syntax},
  author={Yuan Zhang and David I Weiss},
  journal={CoRR},
  year={2016},
  volume={abs/1603.06598}
}
Traditional syntax models typically leverage part-of-speech (POS) information by constructing features from hand-tuned templates. We demonstrate that a better approach is to utilize POS tags as a regularizer of learned representations. We propose a simple method for learning a stacked pipeline of models which we call “stack-propagation”. We apply this to dependency parsing and tagging, where we use the hidden layer of the tagger network as a representation of the input tokens for the parser. At… CONTINUE READING
Highly Cited
This paper has 51 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 10 times over the past 90 days. VIEW TWEETS

Citations

Publications citing this paper.
Showing 1-10 of 38 extracted citations

52 Citations

0102030201620172018
Citations per Year
Semantic Scholar estimates that this publication has 52 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 25 references

Similar Papers

Loading similar papers…