@InProceedings{cheri-bhattacharyya:2017:RepL4NLP,
  author    = {Cheri, Joe  and  Bhattacharyya, Pushpak},
  title     = {Towards Harnessing Memory Networks for Coreference Resolution},
  booktitle = {Proceedings of the 2nd Workshop on Representation Learning for NLP},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {37--42},
  abstract  = {Coreference resolution task demands comprehending a discourse, especially for
	anaphoric mentions which require semantic information for resolving
	antecedents. We investigate into how memory networks can be helpful for
	coreference resolution when posed as question answering problem. The
	comprehension capability of memory networks assists coreference resolution,
	particularly for the mentions that require semantic and context information. We
	experiment memory networks for coreference resolution, with 4 synthetic
	datasets generated for coreference resolu- tion with varying difficulty levels.
	Our system’s performance is compared with a traditional coreference
	resolution system to show why memory network can be promising for coreference
	resolution.},
  url       = {http://www.aclweb.org/anthology/W17-2605}
}