most citedNeural Chinese Word Segmentation as Sequence to Sequence Translation

7 citations · 14 across the 3 of their papers we have counts for

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cs.CL2020

MS-Ranker: Accumulating Evidence from Potentially Correct Candidates for Answer Selection

Yingxue Zhang, Fandong Meng, Peng Li +2

As conventional answer selection (AS) methods generally match the question with each candidate answer independently, they suffer from the lack of matching information between the q…

cs.CL20196 cited

Tag Recommendation by Word-Level Tag Sequence Modeling

Xuewen Shi, Heyan Huang, Shuyang Zhao +2

In this paper, we transform tag recommendation into a word-based text generation problem and introduce a sequence-to-sequence model. The model inherits the advantages of LSTM-based…

cs.CL20197 cited

Neural Chinese Word Segmentation as Sequence to Sequence Translation

Xuewen Shi, Heyan Huang, Ping Jian +3

Recently, Chinese word segmentation (CWS) methods using neural networks have made impressive progress. Most of them regard the CWS as a sequence labeling problem which construct mo…

cs.CL20191 cited

Semantic Graph Convolutional Network for Implicit Discourse Relation Classification

Yingxue Zhang, Ping Jian, Fandong Meng +3

Implicit discourse relation classification is of great importance for discourse parsing, but remains a challenging problem due to the absence of explicit discourse connectives comm…

cs.CL2019

Induction Networks for Few-Shot Text Classification

Ruiying Geng, Binhua Li, Yongbin Li +3

Text classification tends to struggle when data is deficient or when it needs to adapt to unseen classes. In such challenging scenarios, recent studies have used meta-learning to s…