Typical downstream applications such as cross lingual and/or multi-domain sentiment classification, using algorithms proposed by (Hangya et al., 2018), , make use of DNNs 1 https://github.com/naacl18sublong/ Friedland with RNN blocks such as BiLSTMs to learn both generic and domain specific representations.
work focused on multi-domain sentiment classification as in (Liu et al., 2016), (Nam and Han, 2016), proposes building neural architectures for each domain of interest, in addition to shared representation layers across all domains.