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"DRAGNN: A Transition-based Framework for Dynamically Connected Neural ..."

Lingpeng Kong et al. (2017)

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DOI: —

access: open

type: Informal or Other Publication

metadata version: 2021-01-14

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  - electronic edition @ arxiv.org (open access)
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  dblp key:
  - journals/corr/KongAABW17
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  persistent URL:
  - https://dblp.org/rec/journals/corr/KongAABW17
Lingpeng Kong, Chris Alberti, Daniel Andor, Ivan Bogatyy, David Weiss:
DRAGNN: A Transition-based Framework for Dynamically Connected Neural Networks. CoRR abs/1703.04474 (2017)

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