@InProceedings{qi-manning:2017:Short,
  author    = {Qi, Peng  and  Manning, Christopher D.},
  title     = {Arc-swift: A Novel Transition System for Dependency Parsing},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {110--117},
  abstract  = {Transition-based dependency parsers often need sequences of local shift and
	reduce operations to produce certain attachments. Correct individual decisions
	hence require global information about the sentence context and mistakes
	cause error propagation. This paper proposes a novel transition system,
	arc-swift, that enables direct attachments between tokens farther apart with a
	single transition. This allows the parser to leverage lexical information more
	directly in transition decisions. Hence, arc-swift can achieve significantly
	better performance with a very small beam size. Our parsers reduce error by
	3.7--7.6% relative to those using existing transition systems on the Penn
	Treebank dependency parsing task and English Universal Dependencies.},
  url       = {http://aclweb.org/anthology/P17-2018}
}