Learning Bilingual Word Representations by Marginalizing Alignments

@inproceedings{Kocisk2014LearningBW,
  title={Learning Bilingual Word Representations by Marginalizing Alignments},
  author={Tom{\'a}s Kocisk{\'y} and Karl Moritz Hermann and Phil Blunsom},
  booktitle={ACL},
  year={2014}
}
We present a probabilistic model that simultaneously learns alignments and distributed representations for bilingual data. By marginalizing over word alignments the model captures a larger semantic context than prior work relying on hard alignments. The advantage of this approach is demonstrated in a cross-lingual classification task, where we outperform the prior published state of the art. 
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