@InProceedings{hua-wang:2017:FrontiersSummarization,
  author    = {Hua, Xinyu  and  Wang, Lu},
  title     = {A Pilot Study of Domain Adaptation Effect for Neural Abstractive Summarization},
  booktitle = {Proceedings of the Workshop on New Frontiers in Summarization},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {100--106},
  abstract  = {We study the problem of domain adaptation for neural abstractive summarization.
	We make initial efforts in investigating what information can be transferred to
	a new domain. Experimental results on news stories and opinion articles
	indicate that neural summarization model benefits from pre-training based on
	extractive summaries. We also find that the combination of in-domain and
	out-of-domain setup yields better summaries when in-domain data is
	insufficient. Further analysis shows that, the model is capable to select
	salient content even trained on out-of-domain data, but requires in-domain data
	to capture the style for a target domain.},
  url       = {http://www.aclweb.org/anthology/W17-4513}
}