Keynote Speech 1
Title: Challenges in machine learning for NLP
Speaker: Prof Yue Zhang, Westlake University
In this talk, I will briefly review recent progress in the field of natural language processing and the currently dominant method. It shows strong potentials for automatic question answering but also reveals some fragility. Then starting from the question answering task, I will discuss some recent work on probing what is learned in the system, revealing some limitations in the process. I will further discuss several other pieces of evidence for such limitations, before moving on to present several challenges as a consequence. The talk concludes with these as the main issues to solve for a robust NLP system.
Yue Zhang is currently an associate professor at Westlake University. Before joining Westlake in 2018, he worked as an assistant professor at the Singapore University of Technology and Design and as a research associate at the University of Cambridge. Yue Zhang received his PhD degree from the University of Oxford in 2009 and his BEng degree from Tsinghua University, China in 2003. Yue Zhang’s research interest lies in the fundamental algorithms for NLP, syntax, semantics, information extraction, sentiment, text generation, machine translation, and dialogue systems. He serves as the action editor for Transactions of Association of Computational Linguistics (TACL), and area chairs of ACL (2021, 20, 19, 18, 17), EMNLP (2021, 20, 19, 17, 15), COLING (2018, 14) and NAACL (2021, 2019, 15). He gave several tutorials at ACL, EMNLP, and NAACL and OxML, and won awards at SemEval 2020 (best paper honorable mention), COLING 2018 (best paper), and IALP 2017 (best paper).