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20202022
most citedGlobal Context Enhanced Graph Neural Networks for Session-based Recommendation

554 citations · 605 across the 20 of their papers we have counts for

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7 papers · 1 filter

cs.CL2022★ 3 cited

A Unified Neural Network Model for Readability Assessment with Feature Projection and Length-Balanced Loss

Wenbiao Li, Ziyang Wang, Yunfang Wu

For readability assessment, traditional methods mainly employ machine learning classifiers with hundreds of linguistic features. Although the deep learning model has become the pro…

cs.CL2022★ 1 cited

Focus-Driven Contrastive Learniang for Medical Question Summarization

Ming Zhang, Shuai Dou, Ziyang Wang +1

Automatic medical question summarization can significantly help the system to understand consumer health questions and retrieve correct answers. The Seq2Seq model based on maximum…

cs.CL2021★ 1 cited

The NiuTrans Machine Translation Systems for WMT21

Shuhan Zhou, Tao Zhou, Binghao Wei +15

This paper describes NiuTrans neural machine translation systems of the WMT 2021 news translation tasks. We made submissions to 9 language directions, including English$\leftrighta…

cs.CL2020★ 2 cited

Learning Light-Weight Translation Models from Deep Transformer

Bei Li, Ziyang Wang, Hui Liu +4

Recently, deep models have shown tremendous improvements in neural machine translation (NMT). However, systems of this kind are computationally expensive and memory intensive. In t…

cs.CL2020★ 2 cited

Shallow-to-Deep Training for Neural Machine Translation

Bei Li, Ziyang Wang, Hui Liu +5

Deep encoders have been proven to be effective in improving neural machine translation (NMT) systems, but training an extremely deep encoder is time consuming. Moreover, why deep m…

cs.CL2020

Weight Distillation: Transferring the Knowledge in Neural Network Parameters

Ye Lin, Yanyang Li, Ziyang Wang +4

Knowledge distillation has been proven to be effective in model acceleration and compression. It allows a small network to learn to generalize in the same way as a large network. R…

cs.CL2020★ 1 cited

Does Multi-Encoder Help? A Case Study on Context-Aware Neural Machine Translation

Bei Li, Hui Liu, Ziyang Wang +5

In encoder-decoder neural models, multiple encoders are in general used to represent the contextual information in addition to the individual sentence. In this paper, we investigat…