Before revision: Neural word alignmentmethods have received increasing attention recently. These methods usually extract word alignment from a machine translation model. However, there is a gap between translation and alignment tasks, since the target future context is available in the latter .
After revision: Word alignment, which aims to align translationally equivalent words between source and target sentences, plays an important role in many natural language processing tasks. Current unsupervised neural alignment methods focus on inducing alignments from neural machine translation models, which does not leverage the full context in the target sequence .