Corpus ID: 3659314

Baselines and Test Data for Cross-Lingual Inference

@article{Agic2017BaselinesAT,
  title={Baselines and Test Data for Cross-Lingual Inference},
  author={Zeljko Agic and Natalie Schluter},
  journal={ArXiv},
  year={2017},
  volume={abs/1704.05347}
}
  • Zeljko Agic, Natalie Schluter
  • Published in LREC 2017
  • Computer Science
  • The recent years have seen a revival of interest in textual entailment, sparked by i) the emergence of powerful deep neural network learners for natural language processing and ii) the timely development of large-scale evaluation datasets such as SNLI. Recast as natural language inference, the problem now amounts to detecting the relation between pairs of statements: they either contradict or entail one another, or they are mutually neutral. Current research in natural language inference is… CONTINUE READING

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