Abstract:
Recent years have witnessed the advances of deep learning techniques in various areas of NLP. However, as a typical data-driven approach, deep learning suffers from the issues of shallow semantic matching and poor interpretability. A potential solution is to incorporate large-scale symbol-based knowledge graphs into deep learning. In this talk, I will present recent advances on knowledgeable learning for NLP.
Bio:
Zhiyuan Liu is an associate professor at the Department of Computer Science and Technology, Tsinghua University. He received his Ph.D. degree in Computer Science from Tsinghua in 2011. His research interests include representation learning, knowledge graphs and social computation, and has published more than 80 papers in top-tier conferences and journals of AI and NLP including ACL, EMNLP and AAAI, with 12,000+ citations according to Google Scholar.
