@InProceedings{aufrant-wisniewski-yvon:2016:COLING,
  author    = {Aufrant, Lauriane  and  Wisniewski, Guillaume  and  Yvon, Fran\c{c}ois},
  title     = {Zero-resource Dependency Parsing: Boosting Delexicalized Cross-lingual Transfer with Linguistic Knowledge},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {119--130},
  abstract  = {This paper studies cross-lingual transfer for dependency parsing, focusing on
	very low-resource settings where delexicalized transfer is the only fully
	automatic option. We show how to boost parsing performance by rewriting the
	source sentences so as to better match the linguistic regularities of the
	target language. We contrast a data-driven approach with an approach relying on
	linguistically motivated rules automatically extracted from the World Atlas of
	Language Structures. Our findings are backed up by experiments involving 40
	languages. They show that both approaches greatly outperform the baseline, the
	knowledge-driven method yielding the best accuracies, with average improvements
	of +2.9 UAS, and up to +90 UAS (absolute) on some frequent PoS configurations.},
  url       = {http://aclweb.org/anthology/C16-1012}
}