Abstract
In recent years, Neural Machine Translation (NMT) has achieved notable results in various translation tasks. However, the word-by-word generation manner determined by the autoregressive mechanism leads to high translation latency of the NMT and restricts its low-latency applications. Non-Autoregressive Neural Machine Translation (NAT) removes the autoregressive
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CITATION STYLE
APA
Shao, C., Feng, Y., Zhang, J., Meng, F., & Zhou, J. (2021). Sequence-Level Training for Non-Autoregressive Neural Machine Translation. Computational Linguistics, 47(4), 891–925. https://doi.org/10.1162/COLI_a_00421
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