Natural Language Comprehension with the EpiReader

@article{Trischler2016NaturalLC,
  title={Natural Language Comprehension with the EpiReader},
  author={Adam Trischler and Zheng Ye and Xingdi Yuan and Philip Bachman and Alessandro Sordoni and Kaheer Suleman},
  journal={ArXiv},
  year={2016},
  volume={abs/1606.02270}
}
  • Adam Trischler, Zheng Ye, +3 authors Kaheer Suleman
  • Published in EMNLP 2016
  • Computer Science
  • ArXiv
  • We present the EpiReader, a novel model for machine comprehension of text. Machine comprehension of unstructured, real-world text is a major research goal for natural language processing. Current tests of machine comprehension pose questions whose answers can be inferred from some supporting text, and evaluate a model's response to the questions. The EpiReader is an end-to-end neural model comprising two components: the first component proposes a small set of candidate answers after comparing a… CONTINUE READING

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