  Machine translation (MT) is a technique that leverages computers to translate
human languages automatically. Nowadays, neural machine translation (NMT) which
models direct mapping between source and target languages with deep neural
networks has achieved a big breakthrough in translation performance and become
the de facto paradigm of MT. This article makes a review of NMT framework,
discusses the challenges in NMT, introduces some exciting recent progresses and
finally looks forward to some potential future research trends. In addition, we
maintain the state-of-the-art methods for various NMT tasks at the website
https://github.com/ZNLP/SOTA-MT.
