Zhang Ningyu, Ph.D., associate professor at Zhejiang University, his main research interests are knowledge graph, NLP, etc. He has published papers in top international academic conferences and journals such as NeurIPS/ICLR/WWW/KDD/WSDM/AAAI/IJCAI/ACL/ENNLP/NAACL/COLING/SIGIR/TASLP/ESWA/KBS/Journal of Software/Nature Communications. Three paper has been selected as Paper Digest Most Influential Papers (WWW22、IJCAI21、KDD21).
Talks and Events
Efficient Knowledge Graph Construction with Pre-trained Language Models
Knowledge graph construction which aims to extract knowledge from the text corpus, has appealed to researchers. Previous decades have witnessed the remarkable progress of knowledge graph construction on the basis of neural models; however, those models often cost massive computation or labeled data resources. Recently, numerous approaches have been explored to mitigate the efficiency issues for knowledge graph construction, such as prompt learning. In this talk, we aim to bring interested researchers up to speed on the recent and ongoing techniques for efficient knowledge graph construction with pre-trained language models.
Track: Deep Learning for and with Knowledge Graphs
- Knowledge graph construction
- Relation extraction
- Named entity recognition
- Few-shot learning
- Prompt learning