16 citations · 32 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
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…