6 citations · 6 across the 1 of their papers we have counts for
3 papers
cs.CL2020
Transformer-GCRF: Recovering Chinese Dropped Pronouns with General Conditional Random Fields
Jingxuan Yang, Kerui Xu, Jun Xu +5
Pronouns are often dropped in Chinese conversations and recovering the dropped pronouns is important for NLP applications such as Machine Translation. Existing approaches usually f…
cs.CL2019★ 6 cited
Recovering Dropped Pronouns in Chinese Conversations via Modeling Their Referents
Jingxuan Yang, Jianzhuo Tong, Si Li +3
Pronouns are often dropped in Chinese sentences, and this happens more frequently in conversational genres as their referents can be easily understood from context. Recovering drop…
cs.CL2018
From Random to Supervised: A Novel Dropout Mechanism Integrated with Global Information
Hengru Xu, Shen Li, Renfen Hu +2
Dropout is used to avoid overfitting by randomly dropping units from the neural networks during training. Inspired by dropout, this paper presents GI-Dropout, a novel dropout metho…