This paper presents the results of the premier shared task organized alongside the
Conference on Machine Translation (WMT) 2019. Participants were asked to build machine …

We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …

This paper presents the results of the news translation task, the multilingual low-resource
translation for Indo-European languages, the triangular translation task, and the automatic …

The large attention-based encoder-decoder network (Transformer) has become prevailing
recently due to its effectiveness. But the high computation complexity of its decoder raises …

Residual networks are an Euler discretization of solutions to Ordinary Differential Equations
(ODE). This paper explores a deeper relationship between Transformer and numerical ODE …

Improving machine translation (MT) systems with translation memories (TMs) is of great
interest to practitioners in the MT community. However, previous approaches require either a …

Knowledge distillation has been proven to be effective in model acceleration and
compression. It allows a small network to learn to generalize in the same way as a large …

Neural models have drastically advanced state of the art for machine translation (MT)
between high-resource languages. Traditionally, these models rely on large amounts of …

The paper describes the submissions of the eTranslation team to the WMT 2020 news
translation shared task. Leveraging the experience from the team's participation last year we …

Back-translation (BT) of target monolingual corpora is a widely used data augmentation
strategy for neural machine translation (NMT), especially for low-resource language pairs …