The approaches proposed for this issue vary from learning a single model from pooled training data, to more complicated (log-)linear interpolations of multiple models using mixture models (Foster and Kuhn, 2007) and linear mixture models (Carpuat et al., 2014).
in Section 2 we review the state-of-the-art approaches of multi-domain machine translation for both PBMT and NMT.