566 citations · 1.4k across the 18 of their papers we have counts for
18 papers
Microsoft Research Asia's Systems for WMT19
Yingce Xia, Xu Tan, Fei Tian +11
We Microsoft Research Asia made submissions to 11 language directions in the WMT19 news translation tasks. We won the first place for 8 of the 11 directions and the second place fo…
Hint-Based Training for Non-Autoregressive Machine Translation
Zhuohan Li, Zi Lin, Di He +4
Due to the unparallelizable nature of the autoregressive factorization, AutoRegressive Translation (ART) models have to generate tokens sequentially during decoding and thus suffer…
Depth Growing for Neural Machine Translation
Lijun Wu, Yiren Wang, Yingce Xia +5
While very deep neural networks have shown effectiveness for computer vision and text classification applications, how to increase the network depth of neural machine translation (…
Non-Autoregressive Machine Translation with Auxiliary Regularization
Yiren Wang, Fei Tian, Di He +3
As a new neural machine translation approach, Non-Autoregressive machine Translation (NAT) has attracted attention recently due to its high efficiency in inference. However, the hi…
Learning to Teach with Dynamic Loss Functions
Lijun Wu, Fei Tian, Yingce Xia +4
Teaching is critical to human society: it is with teaching that prospective students are educated and human civilization can be inherited and advanced. A good teacher not only prov…
Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter
Lijun Wu, Xu Tan, Di He +4
Neural machine translation usually adopts autoregressive models and suffers from exposure bias as well as the consequent error propagation problem. Many previous works have discuss…