47 citations · 348 across the 39 of their papers we have counts for
61 papers
Adapters for Enhanced Modeling of Multilingual Knowledge and Text
Yifan Hou, Wenxiang Jiao, Meizhen Liu +3
Large language models appear to learn facts from the large text corpora they are trained on. Such facts are encoded implicitly within their many parameters, making it difficult to…
Tencent's Multilingual Machine Translation System for WMT22 Large-Scale African Languages
Wenxiang Jiao, Zhaopeng Tu, Jiarui Li +3
This paper describes Tencent's multilingual machine translation systems for the WMT22 shared task on Large-Scale Machine Translation Evaluation for African Languages. We participat…
Tencent AI Lab - Shanghai Jiao Tong University Low-Resource Translation System for the WMT22 Translation Task
Zhiwei He, Xing Wang, Zhaopeng Tu +2
This paper describes Tencent AI Lab - Shanghai Jiao Tong University (TAL-SJTU) Low-Resource Translation systems for the WMT22 shared task. We participate in the general translation…
Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation
Zhiwei He, Xing Wang, Rui Wang +2
Back-translation is a critical component of Unsupervised Neural Machine Translation (UNMT), which generates pseudo parallel data from target monolingual data. A UNMT model is train…
Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation
Wenxuan Wang, Wenxiang Jiao, Yongchang Hao +4
In this paper, we present a substantial step in better understanding the SOTA sequence-to-sequence (Seq2Seq) pretraining for neural machine translation~(NMT). We focus on studying…
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).…