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    <abstract>Continuous word representations learned separately on distinct languages can be aligned so that their words become comparable in a common space. Existing works typically solve a quadratic problem to learn a orthogonal matrix aligning a bilingual lexicon, and use a retrieval criterion for inference. In this paper, we propose an unified formulation that directly optimizes a retrieval criterion in an end-to-end fashion. Our experiments on standard benchmarks show that our approach outperforms the state of the art on word translation, with the biggest improvements observed for distant language pairs such as English-Chinese.</abstract>
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%0 Conference Proceedings
%T Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion
%A Joulin, Armand
%A Bojanowski, Piotr
%A Mikolov, Tomas
%A Jégou, Hervé
%A Grave, Edouard
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F joulin-etal-2018-loss
%X Continuous word representations learned separately on distinct languages can be aligned so that their words become comparable in a common space. Existing works typically solve a quadratic problem to learn a orthogonal matrix aligning a bilingual lexicon, and use a retrieval criterion for inference. In this paper, we propose an unified formulation that directly optimizes a retrieval criterion in an end-to-end fashion. Our experiments on standard benchmarks show that our approach outperforms the state of the art on word translation, with the biggest improvements observed for distant language pairs such as English-Chinese.
%R 10.18653/v1/D18-1330
%U https://aclanthology.org/D18-1330
%U https://doi.org/10.18653/v1/D18-1330
%P 2979-2984

Markdown (Informal)

[Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion](https://aclanthology.org/D18-1330) (Joulin et al., EMNLP 2018)

• Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion (Joulin et al., EMNLP 2018)

ACL

• Armand Joulin, Piotr Bojanowski, Tomas Mikolov, Hervé Jégou, and Edouard Grave. 2018. Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2979–2984, Brussels, Belgium. Association for Computational Linguistics.