@InProceedings{vanni-EtAl:2018:Long,
  author    = {Vanni, Laurent  and  Ducoffe, Mélanie  and  Aguilar, Carlos  and  Precioso, Frederic  and  Mayaffre, Damon},
  title     = {Textual Deconvolution Saliency (TDS) : a deep tool box for linguistic analysis},
  booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2018},
  address   = {Melbourne, Australia},
  publisher = {Association for Computational Linguistics},
  pages     = {548--557},
  abstract  = {In this paper, we propose a new strategy, called Text Deconvolution Saliency (TDS), to visualize linguistic information detected by a CNN for text classification. We extend Deconvolution Networks to text in order to present a new perspective on text analysis to the linguistic community. We empirically demonstrated the efficiency of our Text Deconvolution Saliency on corpora from three different languages: English, French, and Latin. For every tested dataset, our Text Deconvolution Saliency automatically encodes complex linguistic patterns based on co-occurrences and possibly on grammatical and syntax analysis.},
  url       = {http://www.aclweb.org/anthology/P18-1051}
}