A neural machine translation model is proposed that jointly learns to align and translate by replacing the fixed-length vector bottleneck in the basic encoder-decoder architecture with a soft alignment mechanism.

From Neural Machine Translation by Jointly Learning to Align and Translate · Confidence 0.98