6 citations · 7 across the 3 of their papers we have counts for
5 papers · 1 filter
Only 5\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation
Zihan Liu, Zewei Sun, Shanbo Cheng +2
Document-level Neural Machine Translation (DocNMT) has been proven crucial for handling discourse phenomena by introducing document-level context information. One of the most impor…
Zero-shot Domain Adaptation for Neural Machine Translation with Retrieved Phrase-level Prompts
Zewei Sun, Qingnan Jiang, Shujian Huang +3
Domain adaptation is an important challenge for neural machine translation. However, the traditional fine-tuning solution requires multiple extra training and yields a high cost. I…
Multilingual Translation via Grafting Pre-trained Language Models
Zewei Sun, Mingxuan Wang, Lei Li
Can pre-trained BERT for one language and GPT for another be glued together to translate texts? Self-supervised training using only monolingual data has led to the success of pre-t…
Generating Diverse Translation by Manipulating Multi-Head Attention
Zewei Sun, Shujian Huang, Hao-Ran Wei +2
Transformer model has been widely used on machine translation tasks and obtained state-of-the-art results. In this paper, we report an interesting phenomenon in its encoder-decoder…
Learning to Discriminate Noises for Incorporating External Information in Neural Machine Translation
Zaixiang Zheng, Shujian Huang, Zewei Sun +3
Previous studies show that incorporating external information could improve the translation quality of Neural Machine Translation (NMT) systems. However, there are inevitably noise…