@InProceedings{takase-suzuki-nagata:2017:I17-2,
  author    = {Takase, Sho  and  Suzuki, Jun  and  Nagata, Masaaki},
  title     = {Input-to-Output Gate to Improve RNN Language Models},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {43--48},
  abstract  = {This paper proposes a reinforcing method that refines the output layers of
	existing Recurrent Neural Network (RNN) language models.
	We refer to our proposed method as Input-to-Output Gate (IOG).
	IOG has an extremely simple structure, and thus, can be easily combined with
	any RNN language models.
	Our experiments on the Penn Treebank and WikiText-2 datasets demonstrate that
	IOG consistently boosts the performance of several different types of current
	topline RNN language models.},
  url       = {http://www.aclweb.org/anthology/I17-2008}
}