6 citations · 25 across the 11 of their papers we have counts for
11 papers
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…
BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine Translation
Liyan Kang, Luyang Huang, Ningxin Peng +6
We present a large-scale video subtitle translation dataset, BigVideo, to facilitate the study of multi-modality machine translation. Compared with the widely used How2 and VaTeX d…
Better Datastore, Better Translation: Generating Datastores from Pre-Trained Models for Nearest Neural Machine Translation
Jiahuan Li, Shanbo Cheng, Zewei Sun +2
Nearest Neighbor Machine Translation (kNNMT) is a simple and effective method of augmenting neural machine translation (NMT) with a token-level nearest neighbor retrieval mechanism…
Beyond Triplet: Leveraging the Most Data for Multimodal Machine Translation
Yaoming Zhu, Zewei Sun, Shanbo Cheng +3
Multimodal machine translation (MMT) aims to improve translation quality by incorporating information from other modalities, such as vision. Previous MMT systems mainly focus on be…
Controlling Styles in Neural Machine Translation with Activation Prompt
Yifan Wang, Zewei Sun, Shanbo Cheng +2
Controlling styles in neural machine translation (NMT) has attracted wide attention, as it is crucial for enhancing user experience. Earlier studies on this topic typically concent…
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…
Rethinking Document-level Neural Machine Translation
Zewei Sun, Mingxuan Wang, Hao Zhou +4
This paper does not aim at introducing a novel model for document-level neural machine translation. Instead, we head back to the original Transformer model and hope to answer the f…
Alleviating the Inequality of Attention Heads for Neural Machine Translation
Zewei Sun, Shujian Huang, Xin-Yu Dai +1
Recent studies show that the attention heads in Transformer are not equal. We relate this phenomenon to the imbalance training of multi-head attention and the model dependence on s…
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…