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BibTeX

@InProceedings{yu-falenska-vu:2017:SCLeM,
  author = {Yu, Xiang  and  Falenska, Agnieszka  and  Vu, Ngoc Thang},
  title     = {A General-Purpose Tagger with Convolutional Neural Networks},
  booktitle = {Proceedings of the First Workshop on Subword and Character Level Models in NLP},
  month     = {September},
  year      = 2017,
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {124-129},
  abstract  = {We present a general-purpose tagger based on convolutional neural networks
	(CNN), used for both composing word vectors and encoding context information.
	The CNN tagger is robust across different tagging tasks: without task-specific
	tuning of hyper-parameters, it achieves state-of-the-art results in
	part-of-speech tagging, morphological tagging and supertagging. The CNN tagger
	is also robust against the out-of-vocabulary problem; it performs well on
	artificially unnormalized texts.},
  url       = {https://www.aclweb.org/anthology/W17-4118}
}