This review paper discusses how context has been used in neural machine translation (NMT) in the past two years (2017-2018). Starting with a brief retrospect on the rapid evolution of NMT models, the paper then reviews studies that evaluate NMT output from various perspectives, with emphasis on those analyzing limitations of the translation of contextual phenomena. In a subsequent version, the paper will then present the main methods that were proposed to leverage context for improving translation quality, and distinguishes methods that aim to improve the translation of specific phenomena from those that consider a wider unstructured context.

翻译：本审查文件讨论了过去两年(2017-2018年)神经机器翻译使用环境的情况,首先简要回顾国家机器翻译模式的迅速演变,然后审查从不同角度评价国家机器翻译产出的研究,重点是分析背景现象翻译局限性的研究,然后在随后的版本中,文件将介绍为利用环境改进翻译质量而提议的主要方法,并区分旨在改进具体现象翻译的方法和考虑范围更广、无结构背景现象的方法。