@InProceedings{zhang-EtAl:2017:Long1,
  author    = {Zhang, Jiyuan  and  Feng, Yang  and  Wang, Dong  and  Wang, Yang  and  Abel, Andrew  and  Zhang, Shiyue  and  Zhang, Andi},
  title     = {Flexible and Creative Chinese Poetry Generation Using Neural Memory},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {1364--1373},
  abstract  = {It has been shown that Chinese poems can be successfully generated by
	sequence-to-sequence neural models, particularly with the attention mechanism.
	A potential problem of this approach, however, is that neural models can only
	learn abstract rules, while poem generation is a highly creative process that
	involves not only rules but also innovations for which pure statistical models
	are not appropriate in principle. This work proposes a memory augmented neural
	model for Chinese poem generation, where the neural model and the augmented
	memory work together to balance the requirements of linguistic accordance and
	aesthetic innovation, leading to innovative generations that are still
	rule-compliant. In addition, it is found that the memory mechanism provides
	interesting flexibility that can be used to generate poems with different
	styles.},
  url       = {http://aclweb.org/anthology/P17-1125}
}