In traditional left-to-right machine translation, where the target sequence is predicted token by token, it is natural to determine the length of the sequence dynamically by simply predicting a special EOS (end of sentence) token.
we find that our approach significantly outperforms prior parallel decoding machine translation methods and even approaches the performance of standard autoregressive models (Section 4.2), while decoding significantly faster (Section 4.3).