23 citations · 37 across the 6 of their papers we have counts for
6 papers · 1 filter
ngram-OAXE: Phrase-Based Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation
Cunxiao Du, Zhaopeng Tu, Longyue Wang +1
Recently, a new training oaxe loss has proven effective to ameliorate the effect of multimodality for non-autoregressive translation (NAT), which removes the penalty of word order…
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).…
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…
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…
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…
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…