Before revision:  The aim of this  paper is to highlight the major works that have been undertaken in the space of document-level machine translation before and after the neural revolution  so that researchers can recognise where we started from and which direction we are heading in. When talking about the literature in statistical machine translation (SMT), we focus on works which have tried to improve the translation of specific discourse phenomena, while in neural machine translation (NMT), we focus on works which use the wider context explicitly .
After revision:  The aim of this paper is to highlight the major works that have been undertaken in the space of document-level machine translation before and after the neural revolution so that researchers can recognise the current state and future directions of this field. We provide URLanisation of the literature based on novelties in modelling and architectures as well as training and decoding strategies .