Microsoft Translator at WMT 2019:Towards Large-Scale Document-Level Neural Machine Translation
Table 4: SacreBLEU results for second-pass decoding of single fine-tuned sentence-level model (c) and best sentence-level ensemble. We pass both sentence level models through two second pass models. Missing numbers marked as * were not computed during our experiments.
['[EMPTY]', 'Separated by origin en', 'Separated by origin de', 'Separated by origin both', 'Original test sets 2016', 'Original test sets 2017', 'Original test sets 2018']
In both cases we see degradation in the second pass in terms of BLEU, but the second-pass seems to follow the improved quality of the sentence-level inputs. The two second-pass models over the strong sentence-level ensemble are actually among the better single document-level models we have trained (ignoring at this point that these are a different kind of ensemble or system combination).