@InProceedings{aufrant-wisniewski-yvon:2018:C18-1,
  author    = {Aufrant, Lauriane  and  Wisniewski, Guillaume  and  Yvon, François},
  title     = {Quantifying training challenges of dependency parsers},
  booktitle = {Proceedings of the 27th International Conference on Computational Linguistics},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {3191--3202},
  abstract  = {Not all dependencies are equal when training a dependency parser: some are straightforward enough to be learned with only a sample of data, others embed more complexity. This work introduces a series of metrics to quantify those differences, and thereby to expose the shortcomings of various parsing algorithms and strategies. Apart from a more thorough comparison of parsing systems, these new tools also prove useful for characterizing the information conveyed by cross-lingual parsers, in a quantitative but still interpretable way.},
  url       = {http://www.aclweb.org/anthology/C18-1270}
}