@InProceedings{poliak-EtAl:2017:EACLshort,
  author    = {Poliak, Adam  and  Rastogi, Pushpendre  and  Martin, M. Patrick  and  Van Durme, Benjamin},
  title     = {Efficient, Compositional, Order-sensitive n-gram Embeddings},
  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     = {503--508},
  abstract  = {We propose ECO: a new way to generate embeddings for phrases that is Efficient,
	Compositional, and Order-sensitive. Our method creates decompositional
	embeddings for words offline and combines them to create new embeddings for
	phrases in real time. Unlike other approaches, ECO can create embeddings for
	phrases not seen during training. We evaluate ECO on supervised and
	unsupervised tasks and demonstrate that creating phrase embeddings that are
	sensitive to word order can help downstream tasks.},
  url       = {http://www.aclweb.org/anthology/E17-2081}
}