Question: What was previous state of the art model for automatic post editing?
Answer: pal-EtAl:2018:WMT proposed an APE model that uses three self-attention-based encoders, tebbifakhr-EtAl:2018:WMT, the NMT-subtask winner of WMT 2018 ($wmt18^{nmt}_{best}$), employ sequence-level loss functions in order to avoid exposure bias during training and to be consistent with the automatic evaluation metrics., shin-lee:2018:WMT propose that each encoder has its own self-attention and feed-forward layer to process each input separately. , The APE PBSMT-subtask winner of WMT 2018 ($wmt18^{smt}_{best}$) BIBREF11 also presented another transformer-based multi-source APE which uses two encoders and stacks an additional cross-attention component for $src \rightarrow pe$ above the previous cross-attention for $mt \rightarrow pe$.