Towards Commonsense Reasoning from the Angle of Eventualities

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


PhD Thesis Defence


Title: "Towards Commonsense Reasoning from the Angle of Eventualities"

By

Mr. Hongming ZHANG


Abstract

Commonsense reasoning has long been a core artificial intelligence (AI) 
problem. However, there has long been a lack of scalable commonsense 
acquisition methods and principle ways of applying the commonsense in the 
past. An important reason is that we do not have a good enough commonsense 
representation methodology. In this defense, I will first introduce why we 
should represent commonsense with higher-order selectional preference over 
eventualities (i.e., events and states) and how we can construct a 
large-scale eventuality-centric commonsense knowledge graph (KG) ASER at 
low cost. After that, I will show that the collected knowledge is indeed 
commonsense by demonstrating the transferability from ASER to other 
human-crafted commonsense KGs. As ASER cannot cover all the events, I will 
then introduce how we can generalize knowledge about observed events to 
unseen ones. In the end, I will introduce the proposed commonsense 
inference learning framework CKBQA, which enables us to explore a 
generalizable commonsense inference model.


Date:			Thursday, 3 June 2021

Time:			10:00am - 12:00noon

Zoom Meeting: 
https://hkust.zoom.us/j/91859560324?pwd=dUVTaFVSNm1aWmdqdnM3N05kZUNnUT09

Chairperson:		Prof. Man Ho WONG (HUMA)

Committee Members:	Prof. Yangqiu SONG (Supervisor)
 			Prof. Raymond WONG
 			Prof. Xiaofang ZHOU
 			Prof. Can YANG (MATH)
 			Prof. Irwin KING (CUHK)


**** ALL are Welcome ****