activity
20122021
most citedBreaking Out The XML MisMatch Trap

1 citations · 2 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL2021

Recurrent multiple shared layers in Depth for Neural Machine Translation

GuoLiang Li, Yiyang Li

Learning deeper models is usually a simple and effective approach to improve model performance, but deeper models have larger model parameters and are more difficult to train. To g…

cs.CL2021

Residual Tree Aggregation of Layers for Neural Machine Translation

GuoLiang Li, Yiyang Li

Although attention-based Neural Machine Translation has achieved remarkable progress in recent layers, it still suffers from issue of making insufficient use of the output of each…

cs.LG2020

Representation Learning from Limited Educational Data with Crowdsourced Labels

Wentao Wang, Guowei Xu, Wenbiao Ding +4

Representation learning has been proven to play an important role in the unprecedented success of machine learning models in numerous tasks, such as machine translation, face recog…

cs.DB20191 cited

Technical Report: Optimizing Human Involvement for Entity Matching and Consolidation

Ji Sun, Dong Deng, Ihab Ilyas +5

An end-to-end data integration system requires human feedback in several phases, including collecting training data for entity matching, debugging the resulting clusters, confirmin…

cs.DB2018

Crowd-Powered Data Mining

Chengliang Chai, Ju Fan, Guoliang Li +2

Many data mining tasks cannot be completely addressed by auto- mated processes, such as sentiment analysis and image classification. Crowdsourcing is an effective way to harness th…

cs.AI2018

PANDA: Facilitating Usable AI Development

Jinyang Gao, Wei Wang, Meihui Zhang +7

Recent advances in artificial intelligence (AI) and machine learning have created a general perception that AI could be used to solve complex problems, and in some situations over-…