97 citations · 147 across the 4 of their papers we have counts for
5 papers · 1 filter
Layer-Wise Multi-View Learning for Neural Machine Translation
Qiang Wang, Changliang Li, Yue Zhang +2
Traditional neural machine translation is limited to the topmost encoder layer's context representation and cannot directly perceive the lower encoder layers. Existing solutions us…
Training Flexible Depth Model by Multi-Task Learning for Neural Machine Translation
Qiang Wang, Tong Xiao, Jingbo Zhu
The standard neural machine translation model can only decode with the same depth configuration as training. Restricted by this feature, we have to deploy models of various sizes t…
Neural Machine Translation with Joint Representation
Yanyang Li, Qiang Wang, Tong Xiao +2
Though early successes of Statistical Machine Translation (SMT) systems are attributed in part to the explicit modelling of the interaction between any two source and target units,…
Multi-layer Representation Fusion for Neural Machine Translation
Qiang Wang, Fuxue Li, Tong Xiao +3
Neural machine translation systems require a number of stacked layers for deep models. But the prediction depends on the sentence representation of the top-most layer with no acces…
Learning Deep Transformer Models for Machine Translation
Qiang Wang, Bei Li, Tong Xiao +4
Transformer is the state-of-the-art model in recent machine translation evaluations. Two strands of research are promising to improve models of this kind: the first uses wide netwo…