activity
20172021
most citedRobust Neural Machine Translation with Doubly Adversarial Inputs

37 citations · 51 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CL20218 cited

Self-supervised and Supervised Joint Training for Resource-rich Machine Translation

Yong Cheng, Wei Wang, Lu Jiang +1

Self-supervised pre-training of text representations has been successfully applied to low-resource Neural Machine Translation (NMT). However, it usually fails to achieve notable ga…

cs.CL20206 cited

AdvAug: Robust Adversarial Augmentation for Neural Machine Translation

Yong Cheng, Lu Jiang, Wolfgang Macherey +1

In this paper, we propose a new adversarial augmentation method for Neural Machine Translation (NMT). The main idea is to minimize the vicinal risk over virtual sentences sampled f…

cs.CL201937 cited

Robust Neural Machine Translation with Doubly Adversarial Inputs

Yong Cheng, Lu Jiang, Wolfgang Macherey

Neural machine translation (NMT) often suffers from the vulnerability to noisy perturbations in the input. We propose an approach to improving the robustness of NMT models, which c…

cs.CL2018

Neural Machine Translation with Key-Value Memory-Augmented Attention

Fandong Meng, Zhaopeng Tu, Yong Cheng +4

Although attention-based Neural Machine Translation (NMT) has achieved remarkable progress in recent years, it still suffers from issues of repeating and dropping translations. To…

cs.CL2018

Towards Robust Neural Machine Translation

Yong Cheng, Zhaopeng Tu, Fandong Meng +2

Small perturbations in the input can severely distort intermediate representations and thus impact translation quality of neural machine translation (NMT) models. In this paper, we…

cs.CL2017

A Teacher-Student Framework for Zero-Resource Neural Machine Translation

Yun Chen, Yang Liu, Yong Cheng +1

While end-to-end neural machine translation (NMT) has made remarkable progress recently, it still suffers from the data scarcity problem for low-resource language pairs and domains…