@InProceedings{vulic:2017:EACLshort,
  author    = {Vuli\'{c}, Ivan},
  title     = {Cross-Lingual Syntactically Informed Distributed Word Representations},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {408--414},
  abstract  = {We develop a novel cross-lingual word representation model which injects
	syntactic information through dependency-based contexts into a shared
	cross-lingual word vector space. The model, termed CL-DepEmb, is based on the
	following assumptions: (1) dependency relations are largely
	language-independent, at least for related languages and prominent dependency
	links such as direct objects, as evidenced by the Universal Dependencies
	project; (2) word translation equivalents take similar grammatical roles in a
	sentence and are therefore substitutable within their syntactic contexts.
	Experiments with several language pairs on word similarity and bilingual
	lexicon induction, two fundamental semantic tasks emphasising semantic
	similarity, suggest the usefulness of the proposed syntactically informed
	cross-lingual word vector spaces. Improvements are observed in both tasks over
	standard cross-lingual "offline mapping" baselines trained using the same setup
	and an equal level of bilingual supervision.},
  url       = {http://www.aclweb.org/anthology/E17-2065}
}