@InProceedings{wang-zhang-zong:2017:EMNLP2017,
  author    = {Wang, Shaonan  and  Zhang, Jiajun  and  Zong, Chengqing},
  title     = {Exploiting Word Internal Structures for Generic Chinese Sentence Representation},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {298--303},
  abstract  = {We introduce a novel mixed characterword architecture to improve Chinese
	sentence representations, by utilizing rich semantic information of word
	internal structures. Our architecture uses two key strategies. The first is a
	mask gate on characters, learning the relation among characters in a word. The
	second is a maxpooling operation on words, adaptively finding the optimal
	mixture of the atomic and compositional word representations. Finally, the
	proposed architecture is applied to various sentence composition models, which
	achieves substantial performance gains over baseline models on sentence
	similarity task.},
  url       = {https://www.aclweb.org/anthology/D17-1029}
}