most citedTranSmart: A Practical Interactive Machine Translation System

23 citations · 33 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2021

On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation

Xuebo Liu, Longyue Wang, Derek F. Wong +4

Pre-training (PT) and back-translation (BT) are two simple and powerful methods to utilize monolingual data for improving the model performance of neural machine translation (NMT).…

cs.CL20211 cited

On the Copying Behaviors of Pre-Training for Neural Machine Translation

Xuebo Liu, Longyue Wang, Derek F. Wong +4

Previous studies have shown that initializing neural machine translation (NMT) models with the pre-trained language models (LM) can speed up the model training and boost the model…

cs.CL20213 cited

Progressive Multi-Granularity Training for Non-Autoregressive Translation

Liang Ding, Longyue Wang, Xuebo Liu +3

Non-autoregressive translation (NAT) significantly accelerates the inference process via predicting the entire target sequence. However, recent studies show that NAT is weak at lea…

cs.CL202123 cited

TranSmart: A Practical Interactive Machine Translation System

Guoping Huang, Lemao Liu, Xing Wang +5

Automatic machine translation is super efficient to produce translations yet their quality is not guaranteed. This technique report introduces TranSmart, a practical human-machine…

cs.CL20196 cited

Modeling Recurrence for Transformer

Jie Hao, Xing Wang, Baosong Yang +3

Recently, the Transformer model that is based solely on attention mechanisms, has advanced the state-of-the-art on various machine translation tasks. However, recent studies reveal…