@InProceedings{suzuki-nagata:2017:EACLshort,
  author    = {Suzuki, Jun  and  Nagata, Masaaki},
  title     = {Cutting-off Redundant Repeating Generations for Neural Abstractive Summarization},
  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     = {291--297},
  abstract  = {This paper tackles the reduction of redundant repeating generation that is
	often observed in RNN-based encoder-decoder models.
	 Our basic idea is to jointly estimate the upper-bound frequency of each target
	vocabulary in the encoder and control the output words based on the estimation
	in the decoder.
	 Our method shows significant improvement over a strong RNN-based
	encoder-decoder baseline and achieved its best results on an abstractive
	summarization benchmark.},
  url       = {http://www.aclweb.org/anthology/E17-2047}
}