Automatically Extracting Challenge Sets for Non local Phenomena in Neural Machine Translation

@article{Choshen2019AutomaticallyEC,
  title={Automatically Extracting Challenge Sets for Non local Phenomena in Neural Machine Translation},
  author={Leshem Choshen and Omri Abend},
  journal={ArXiv},
  year={2019},
  volume={abs/1909.06814}
}
  • Leshem Choshen, Omri Abend
  • Published 2019
  • Computer Science
  • ArXiv
  • We show that the state-of-the-art Transformer MT model is not biased towards monotonic reordering (unlike previous recurrent neural network models), but that nevertheless, long-distance dependencies remain a challenge for the model. [...] Key Result The extracted sets are large enough to allow reliable automatic evaluation, which makes the proposed approach a scalable and practical solution for evaluating MT performance on the long-tail of syntactic phenomena.Expand Abstract

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