most citedRelational Triple Extraction: One Step is Enough

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

collaborators

5 papers

cs.CL2022

HCL-TAT: A Hybrid Contrastive Learning Method for Few-shot Event Detection with Task-Adaptive Threshold

Ruihan Zhang, Wei Wei, Xian-Ling Mao +2

Conventional event detection models under supervised learning settings suffer from the inability of transfer to newly-emerged event types owing to lack of sufficient annotations. A…

cs.CL2022

Capturing Global Structural Information in Long Document Question Answering with Compressive Graph Selector Network

Yuxiang Nie, Heyan Huang, Wei Wei +1

Long document question answering is a challenging task due to its demands for complex reasoning over long text. Previous works usually take long documents as non-structured flat te…

cs.CL2022

Sequential Topic Selection Model with Latent Variable for Topic-Grounded Dialogue

Xiaofei Wen, Wei Wei, Xian-Ling Mao

Recently, topic-grounded dialogue system has attracted significant attention due to its effectiveness in predicting the next topic to yield better responses via the historical cont…

cs.CV2022

Unsupervised Hashing with Semantic Concept Mining

Rong-Cheng Tu, Xian-Ling Mao, Kevin Qinghong Lin +5

Recently, to improve the unsupervised image retrieval performance, plenty of unsupervised hashing methods have been proposed by designing a semantic similarity matrix, which is bas…

cs.CL20222 cited

Relational Triple Extraction: One Step is Enough

Yu-Ming Shang, Heyan Huang, Xin Sun +2

Extracting relational triples from unstructured text is an essential task in natural language processing and knowledge graph construction. Existing approaches usually contain two f…