24 citations · 121 across the 50 of their papers we have counts for
6 papers · 2 filters
A Survey of Knowledge Enhanced Pre-trained Language Models
Linmei Hu, Zeyi Liu, Ziwang Zhao +3
Pre-trained Language Models (PLMs) which are trained on large text corpus via self-supervised learning method, have yielded promising performance on various tasks in Natural Langua…
EDUKG: a Heterogeneous Sustainable K-12 Educational Knowledge Graph
Bowen Zhao, Jiuding Sun, Bin Xu +9
Web and artificial intelligence technologies, especially semantic web and knowledge graph (KG), have recently raised significant attention in educational scenarios. Nevertheless, s…
Step out of KG: Knowledge Graph Completion via Knowledgeable Retrieval and Reading Comprehension
Xin Lv, Yankai Lin, Zijun Yao +4
Knowledge graphs, as the cornerstone of many AI applications, usually face serious incompleteness problems. In recent years, there have been many efforts to study automatic knowled…
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…
Unveiling the Black Box of PLMs with Semantic Anchors: Towards Interpretable Neural Semantic Parsing
Lunyiu Nie, Jiuding Sun, Yanlin Wang +6
The recent prevalence of pretrained language models (PLMs) has dramatically shifted the paradigm of semantic parsing, where the mapping from natural language utterances to structur…
Schema-Free Dependency Parsing via Sequence Generation
Boda Lin, Zijun Yao, Jiaxin Shi +6
Dependency parsing aims to extract syntactic dependency structure or semantic dependency structure for sentences. Existing methods suffer the drawbacks of lacking universality or h…