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The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21

Authors :
Qian, Lihua
Zhou, Yi
Zheng, Zaixiang
Zhu, Yaoming
Lin, Zehui
Feng, Jiangtao
Cheng, Shanbo
Li, Lei
Wang, Mingxuan
Zhou, Hao
Publication Year :
2021

Abstract

This paper describes the Volctrans' submission to the WMT21 news translation shared task for German->English translation. We build a parallel (i.e., non-autoregressive) translation system using the Glancing Transformer, which enables fast and accurate parallel decoding in contrast to the currently prevailing autoregressive models. To the best of our knowledge, this is the first parallel translation system that can be scaled to such a practical scenario like WMT competition. More importantly, our parallel translation system achieves the best BLEU score (35.0) on German->English translation task, outperforming all strong autoregressive counterparts.<br />Comment: 10 pages, 5 figures, WMT2021

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2109.11247
Document Type :
Working Paper