Syntax-Aware Complex-Valued Neural Machine Translation
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-44192-9_38
Reference26 articles.
1. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014)
2. Chen, H., Huang, S., Chiang, D., Chen, J.: Improved neural machine translation with a syntax-aware encoder and decoder. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Vancouver, Canada (Volume 1: Long Papers), pp. 1936–1945. Association for Computational Linguistics (2017). https://doi.org/10.18653/v1/P17-1177. https://aclanthology.org/P17-1177
3. Chen, K., et al.: Neural machine translation with source dependency representation. In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, Copenhagen, Denmark, pp. 2846–2852. Association for Computational Linguistics (2017). https://doi.org/10.18653/v1/D17-1304. https://aclanthology.org/D17-1304
4. Chiang, D.: Hierarchical phrase-based translation. Comput. Linguist. 33(2), 201–228 (2007). https://doi.org/10.1162/coli.2007.33.2.201
5. Cho, K., van Merriënboer, B., Bahdanau, D., Bengio, Y.: On the properties of neural machine translation: encoder-decoder approaches. In: Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation, Doha, Qatar, pp. 103–111. Association for Computational Linguistics (2014). https://doi.org/10.3115/v1/W14-4012. https://aclanthology.org/W14-4012
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