Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since
the early 2000s and has already entered a mature phase. While considered the most widely …

We present a survey on multilingual neural machine translation (MNMT), which has gained
a lot of traction in recent years. MNMT has been useful in improving translation quality as a …

The main challenge in the field of unsupervised machine translation (UMT) is to associate
source-target sentences in the latent space. As people who speak different languages share …

This paper demonstrates that multilingual denoising pre-training produces significant
performance gains across a wide variety of machine translation (MT) tasks. We present …

Existing multilingual machine translation approaches mainly focus on English-centric
directions, while the non-English directions still lag behind. In this work, we aim to build a …

We introduce our efforts towards building a universal neural machine translation (NMT)
system capable of translating between any language pair. We set a milestone towards this …

Machine translation has recently achieved impressive performance thanks to recent
advances in deep learning and the availability of large-scale parallel corpora. There have …

Machine translation systems achieve near human-level performance on some languages,
yet their effectiveness strongly relies on the availability of large amounts of parallel …

In this paper, we propose to extend the recently introduced model-agnostic meta-learning
algorithm (MAML) for low-resource neural machine translation (NMT). We frame low …

It has been shown that the performance of neural machine translation (NMT) drops starkly in
low-resource conditions, underperforming phrase-based statistical machine translation …