In that time, researchers have explored architectures ranging from convolutional neural networks (Kalchbrenner and Blunsom, 2013) to recurrent neural networks (Chung et al., 2014) to attentional models (Bahdanau et al., 2015;<cite> Luong et al., 2015)</cite> and achieved better performance than traditional statistical or syntax-based MT techniques on many language pairs.