8 citations · 8 across the 4 of their papers we have counts for
4 papers
Text Style Transfer Back-Translation
Daimeng Wei, Zhanglin Wu, Hengchao Shang +6
Back Translation (BT) is widely used in the field of machine translation, as it has been proved effective for enhancing translation quality. However, BT mainly improves the transla…
KG-BERTScore: Incorporating Knowledge Graph into BERTScore for Reference-Free Machine Translation Evaluation
Zhanglin Wu, Min Zhang, Ming Zhu +5
BERTScore is an effective and robust automatic metric for referencebased machine translation evaluation. In this paper, we incorporate multilingual knowledge graph into BERTScore a…
Joint-training on Symbiosis Networks for Deep Nueral Machine Translation models
Zhengzhe Yu, Jiaxin Guo, Minghan Wang +11
Deep encoders have been proven to be effective in improving neural machine translation (NMT) systems, but it reaches the upper bound of translation quality when the number of encod…
Self-Distillation Mixup Training for Non-autoregressive Neural Machine Translation
Jiaxin Guo, Minghan Wang, Daimeng Wei +11
Recently, non-autoregressive (NAT) models predict outputs in parallel, achieving substantial improvements in generation speed compared to autoregressive (AT) models. While performi…