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The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation.

, , , , , , , , , , , , , , , and . ACL (1), page 76-86. Association for Computational Linguistics, (2018)

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Fast, Greedy Model Minimization for Unsupervised Tagging., , , and . COLING, page 940-948. Tsinghua University Press, (2010)Hassan: A Virtual Human for Tactical Questioning., , , , , , , , and . SIGdial, page 71-74. Association for Computational Linguistics, (2007)The Efficiency Misnomer., , , , and . ICLR, OpenReview.net, (2022)Name Tagging for Low-resource Incident Languages based on Expectation-driven Learning., , , , , , and . HLT-NAACL, page 249-259. The Association for Computational Linguistics, (2016)Model Invertibility Regularization: Sequence Alignment With or Without Parallel Data., , and . HLT-NAACL, page 609-618. The Association for Computational Linguistics, (2015)Mesh-tensorflow: Deep learning for supercomputers, , , , , , , , , and 1 other author(s). Advances in Neural Information Processing Systems, page 10435--10444. (2018)Beyond Parallel Data: Joint Word Alignment and Decipherment Improves Machine Translation., , and . EMNLP, page 557-565. ACL, (2014)Simple, Fast Noise-Contrastive Estimation for Large RNN Vocabularies., , , and . HLT-NAACL, page 1217-1222. The Association for Computational Linguistics, (2016)Supertagging With LSTMs., , , and . HLT-NAACL, page 232-237. The Association for Computational Linguistics, (2016)Efficient Content-Based Sparse Attention with Routing Transformers., , , and . CoRR, (2020)