End-to-end neural machine translation (NMT), which leverages neural networks to directly map between natural languages, has gained increasing popularity recently Bahdanau et al., 2015).
we find that while the attention identifies the 10-th source word "kuadaxiyang" (cross-atlantic) to be most relevant, the relevance vector of the target word R y 9 finds that multiple source and target words should contribute to the generation of the next target word.