  The University of Cambridge submission to the WMT18 news translation task
focuses on the combination of diverse models of translation. We compare
recurrent, convolutional, and self-attention-based neural models on
German-English, English-German, and Chinese-English. Our final system combines
all neural models together with a phrase-based SMT system in an MBR-based
scheme. We report small but consistent gains on top of strong Transformer
ensembles.
