@InProceedings{li-cohn-baldwin:2017:BLGNLP2017,
  author    = {Li, Yitong  and  Cohn, Trevor  and  Baldwin, Timothy},
  title     = {BIBI System Description: Building with CNNs and Breaking with Deep Reinforcement Learning},
  booktitle = {Proceedings of the First Workshop on Building Linguistically Generalizable NLP Systems},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {27--32},
  abstract  = {This paper describes our submission to the sentiment analysis sub-task of
	``Build It, Break It: The Language Edition (BIBI)'', on both the builder and
	breaker sides.
	As a builder, we use convolutional neural nets, trained on both phrase and
	sentence data.
	As a breaker, we use Q-learning to learn minimal change pairs, and apply a
	token substitution method automatically.
	We analyse the results to gauge the robustness of NLP systems.},
  url       = {http://www.aclweb.org/anthology/W17-5404}
}