2 citations · 5 across the 5 of their papers we have counts for
6 papers · 1 filter
ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction
Ji Qi, Bin Xu, Kaisheng Zeng +5
Document-level relation extraction with graph neural networks faces a fundamental graph construction gap between training and inference - the golden graph structure only available…
PatentMiner: Patent Vacancy Mining via Context-enhanced and Knowledge-guided Graph Attention
Gaochen Wu, Bin Xu, Yuxin Qin +4
Although there are a small number of work to conduct patent research by building knowledge graph, but without constructing patent knowledge graph using patent documents and combini…
Improving Low-resource Reading Comprehension via Cross-lingual Transposition Rethinking
Gaochen Wu, Bin Xu, Yuxin Qin +4
Extractive Reading Comprehension (ERC) has made tremendous advances enabled by the availability of large-scale high-quality ERC training data. Despite of such rapid progress and wi…
Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition
Meihan Tong, Shuai Wang, Bin Xu +4
Few-shot Named Entity Recognition (NER) exploits only a handful of annotations to identify and classify named entity mentions. Prototypical network shows superior performance on fe…
A Multilingual Modeling Method for Span-Extraction Reading Comprehension
Gaochen Wu, Bin Xu, Dejie Chang +1
Span-extraction reading comprehension models have made tremendous advances enabled by the availability of large-scale, high-quality training datasets. Despite such rapid progress a…
DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction
Dejie Chang, Mosha Chen, Chaozhen Liu +9
Knowledge Graph has been proven effective in modeling structured information and conceptual knowledge, especially in the medical domain. However, the lack of high-quality annotated…