Neural Machine Translation by Jointly Learning to Align and Translate

Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio submitted 'Neural Machine Translation by Jointly Learning to Align and Translate' on September 1, 2014. The paper proposed extending encoder-decoder neural machine translation by allowing the model to automatically soft-search for source-sentence parts relevant to predicting each target word rather than relying only on a single fixed-length source representation.