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Multi-source translation systems translate from multiple languages to a single target language.
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B. Zoph and K. Knight, “Multi-Source Neural Translation,” in Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
2016
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E. Garmash and C. Monz, “Ensemble Learning for Multi-Source Neural Machine Translation,” in Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
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R. Sennrich, B. Haddow, and A. Birch, “Improving neural machine translation models with monolingual data,” in Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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K. Imamura, A. Fujita, and E. Sumita, “Enhancement of encoder and attention using target monolingual corpora in neural machine translation,” in Proceedings of the 2nd Workshop on Neural Machine Translation and Generation
2018
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X. Wang, H. Pham, Z. Dai, and G. Neubig, “Switchout: an efficient data augmentation algorithm for neural machine translation,” in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
2018
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T. Kudo, “Subword regularization: Improving neural network translation models with multiple subword candidates,” in Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
2018
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