Neural-network-based models for Machine Translation (MT) have set new standards for performance, especially when large amounts of parallel text (bitext) are available.
explicit word-to-word alignments, which were foundational to pre-neural statistical MT (SMT) (Brown et al., 1993), have largely been lost in neural MT (NMT) models.