Data Rejuvenation: Exploiting Inactive Training Examples for Neural
Machine Translation

Data Rejuvenation: Exploiting Inactive Training Examples for Neural Machine Translation

6 October 2020

Irwin King

Michael R. Lyu

Papers citing "Data Rejuvenation: Exploiting Inactive Training Examples for Neural Machine Translation"

6 / 6 papers shown

Title
Tencent's Multilingual Machine Translation System for WMT22 Large-Scale African Languages Wenxiang Jiao Zhaopeng Tu Jiarui Li Wenxuan Wang Jen-tse Huang Shuming Shi 54 15 0 18 Oct 2022
Tencent AI Lab - Shanghai Jiao Tong University Low-Resource Translation System for the WMT22 Translation Task Zhiwei He Xing Wang Zhaopeng Tu Shuming Shi Rui Wang 31 9 0 17 Oct 2022
On the Complementarity between Pre-Training and Random-Initialization for Resource-Rich Machine Translation Changtong Zan Liang Ding Li Shen Yu Cao Weifeng Liu Dacheng Tao 37 21 0 07 Sep 2022
Understanding and Mitigating the Uncertainty in Zero-Shot Translation Wenxuan Wang Wenxiang Jiao Shuo Wang Zhaopeng Tu Michael R. Lyu UQLM 42 9 0 20 May 2022
Understanding and Improving Sequence-to-Sequence Pretraining for Neural Machine Translation Wenxuan Wang Wenxiang Jiao Yongchang Hao Xing Wang Shuming Shi Zhaopeng Tu Michael Lyu AIMat 39 26 0 16 Mar 2022
Six Challenges for Neural Machine Translation Philipp Koehn Rebecca Knowles AAML AIMat 224 1,209 0 12 Jun 2017