102 citations · 335 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
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…
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…
Neural Machine Translation with Pivot Languages
Yong Cheng, Yang Liu, Qian Yang +2
While recent neural machine translation approaches have delivered state-of-the-art performance for resource-rich language pairs, they suffer from the data scarcity problem for reso…
Semi-Supervised Learning for Neural Machine Translation
Yong Cheng, Wei Xu, Zhongjun He +4
While end-to-end neural machine translation (NMT) has made remarkable progress recently, NMT systems only rely on parallel corpora for parameter estimation. Since parallel corpora…
Agreement-based Joint Training for Bidirectional Attention-based Neural Machine Translation
Yong Cheng, Shiqi Shen, Zhongjun He +4
The attentional mechanism has proven to be effective in improving end-to-end neural machine translation. However, due to the intricate structural divergence between natural languag…
Minimum Risk Training for Neural Machine Translation
Shiqi Shen, Yong Cheng, Zhongjun He +4
We propose minimum risk training for end-to-end neural machine translation. Unlike conventional maximum likelihood estimation, minimum risk training is capable of optimizing model…