Automated Question Generation and Question Answering
Introduction
Asking questions plays a vital role for both the growth of human beings and the improvement of artificial intelligent systems. As a dual task of question answering, question generation based on a text passage and a given answer has attracted much attention in recent years. One of the key applications of question generation is to automatically produce question-answer pairs to enhance machine reading comprehension systems. Another application is generating practice exercises and assessments for educational purposes. Besides, question generation is also important in conversational systems and chatbots such as Siri, Cortana, Alexa and Google Assistant, helping them to kick-start and continue a conversation with human users
This project aims to develop efficient algorithms and techniques for question generation and question answering.
Relevant Materials
Publications
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Yuyan Chen, Yanghua Xiao✉, Zhixu Li✉, Bang Liu✉. (2023).
XMQAs: Constructing Complex-Modified Question Answering Dataset for Robust Question Understanding,
in IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 3, pp. 1371-1384, March 2024
(Download)
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Xiaoqiang Wang-, Bang Liu✉, Siliang Tang✉, Lingfei Wu✉. (2023).
SkillQG: Learning to Generate Question for Reading Comprehension Assessment,
in Findings of ACL 2023.
(Download)
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Xiaoqiang Wang*, Bang Liu*, Siliang Tang✉, Lingfei Wu✉. (2022).
QRelScore: Better Evaluating Generated Questions with Deeper Understanding of Context-aware Relevance,
in EMNLP 2022.
(Online)
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Junyang Huang, Xuantao Lu, Jiaqing Liang, Qiaoben Bao, Chen Huang, Yanghua Xiao✉, Bang Liu, Yunwen Chen. (2022).
Knowing What I Don’t Know: A Generation Assisted Rejection Framework in Knowledge Base Question Answering,
in DASFAA 2022.
(Download)
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Yi Cheng+, Siyao Li+, Bang Liu✉, Ruihui Zhao, Sujian Li, Chenghua Lin, Yefeng Zheng. (2021).
Guiding the Growth: Difficulty-Controllable Multi-hop Question Generation through Step-by-step Rewriting,
in ACL 2021.
(Download)
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Bang Liu, Haojie Wei, Di Niu, Haolan Chen, Yancheng He. (2020).
Asking questions the Human Way: Scalable Question-Answer Generation from Text Corpus,
in WWW 2020.
(Download)
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Bang Liu, Mingjun Zhao, Di Niu, Kunfeng Lai, Yancheng He, Haojie Wei and Yu Xu. (2019).
Learning to Generate Questions by Learning What not to Generate,
in WWW 2019.
(Download)