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This paper describes the Microsoft submission to the WMT2018 news translationshared task. We participated in one language direction -- English-German. Oursystem follows current best-practice and combines state-of-the-art models withnew data filtering (dual conditional cross-entropy filtering) and sentenceweighting methods. We trained fairly standard Transformer-big models with anupdated version of Edinburgh's training scheme for WMT2017 and experimentedwith different filtering schemes for Paracrawl. According to automatic metrics(BLEU) we reached the highest score for this subtask with a nearly 2 BLEU pointmargin over the next strongest system. Based on human evaluation we rankedfirst among constrained systems. We believe this is mostly caused by our datafiltering/weighting regime.

Microsoft's Submission to the WMT2018 News Translation Task: How I Learned to Stop Worrying and Love the Data