We thank all reviewers for their valuable feedback and thoughtfull suggestions. To the best of our knowledge, there is no official implementation for the paper by Gu et al. (no link to the code However, in Section 5.1 we compare the lower bound on the objective we use with the one of Gu et These works do not report significant improvements in BLEU scores against the autoregressive baselines. Stern et al.(2019) focus on parallel decoding (with the final result matching the vanilla Transformer). NMT models for high-resource language pairs), we will add them should the paper get accepted. Note that we consider not only natural language output, but also Image-to-Latex, where output is LaTex formulas.

We thank all reviewers for their valuable feedback and thoughtfull suggestions. To the best of our knowledge, there is no official implementation for the paper by Gu et al. (no link to the code However, in Section 5.1 we compare the lower bound on the objective we use with the one of Gu et These works do not report significant improvements in BLEU scores against the autoregressive baselines. Stern et al.(2019) focus on parallel decoding (with the final result matching the vanilla Transformer). NMT models for high-resource language pairs), we will add them should the paper get accepted. Note that we consider not only natural language output, but also Image-to-Latex, where output is LaTex formulas.