activity
20152019
most citedEncoding Source Language with Convolutional Neural Network for Machine Translation

51 citations · 138 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL201931 cited

Imitation Learning for Non-Autoregressive Neural Machine Translation

Bingzhen Wei, Mingxuan Wang, Hao Zhou +3

Non-autoregressive translation models (NAT) have achieved impressive inference speedup. A potential issue of the existing NAT algorithms, however, is that the decoding is conducted…

cs.CL201715 cited

Deep Semantic Role Labeling with Self-Attention

Zhixing Tan, Mingxuan Wang, Jun Xie +2

Semantic Role Labeling (SRL) is believed to be a crucial step towards natural language understanding and has been widely studied. Recent years, end-to-end SRL with recurrent neural…

cs.CL2017

Deep Neural Machine Translation with Linear Associative Unit

Mingxuan Wang, Zhengdong Lu, Jie Zhou +1

Deep Neural Networks (DNNs) have provably enhanced the state-of-the-art Neural Machine Translation (NMT) with their capability in modeling complex functions and capturing complex l…

cs.CL2016

Memory-enhanced Decoder for Neural Machine Translation

Mingxuan Wang, Zhengdong Lu, Hang Li +1

We propose to enhance the RNN decoder in a neural machine translator (NMT) with external memory, as a natural but powerful extension to the state in the decoding RNN. This memory-e…

cs.CL201511 cited

CNN: A Convolutional Architecture for Word Sequence Prediction

Mingxuan Wang, Zhengdong Lu, Hang Li +2

We propose a novel convolutional architecture, named CNN, for word sequence prediction. Different from previous work on neural network-based language modeling and generation (…

cs.CL201530 cited

Syntax-based Deep Matching of Short Texts

Mingxuan Wang, Zhengdong Lu, Hang Li +1

Many tasks in natural language processing, ranging from machine translation to question answering, can be reduced to the problem of matching two sentences or more generally two sho…