@InProceedings{yang-costajussa-fonollosa:2017:RepEval,
  author    = {Yang, Han  and  Costa-juss\`{a}, Marta R.  and  Fonollosa, Jos\'{e} A. R.},
  title     = {Character-level Intra Attention Network for Natural Language Inference},
  booktitle = {Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {46--50},
  abstract  = {Natural language inference (NLI) is a central problem in language
	understanding. End-to-end artificial neural networks have reached
	state-of-the-art  performance in NLI field recently. In this paper, we propose
	Character-level Intra Attention Network (CIAN) for the NLI task. In our model,
	we use the character-level convolutional network to replace the standard word
	embedding layer, and we use the intra attention to capture the intra-sentence
	semantics. The proposed CIAN model provides improved results based on a newly
	published MNLI corpus.},
  url       = {http://www.aclweb.org/anthology/W17-5309}
}