Selected Topics in Question Answering

Seminar, 7 ECTS credits, Winter semester 2020/21

Basic Information

Course contents

In this seminar course, we will cover topics around automated question answering (QA) systems over knowledge graphs, text corpora, and heterogeneous sources. The last few years have seen an explosion of research on the topic of QA, spanning the communities of information retrieval, natural language processing, and artificial intelligence. Through this seminar, students will be able to describe and critique state-of-the-art approaches for question answering. More generally, they will gain experience in analyzing relevant scientific literature. We will compile a set of references that cover the key topics of active interest in the community, like complex QA, heterogeneous QA, and conversational QA. Topics will also include addressing key dimensions like user feedback, interpretability, unanswerability, and efficiency.

Lectures and assignments

There will be two introductory lectures where the various sub-topics and reviewing guidelines will be introduced. Attendance in both of these sessions is mandatory. Each student will be assigned two research papers on a topic. At the end of course, the student will have to write a short review on these papers and deliver a presentation, based on their understanding of the assigned topic. The presentations by the students will be as a block seminar spanning two days in December.

Prerequisites

A basic knowledge of database management systems, information retrieval, natural language processing, and machine learning will be helpful. Additional knowledge of probability and statistics, linear algebra, and optimization techniques is reocmmended, but not absolutely necessary. The courses on Question Answering Systems (Summer Semester 2020) and Information Retrieval and Data Mining (Winter Semester 2019/20) are recommended but not mandatory.

Schedule and topics

LectureDate Topic SlidesVideos
0103 November 2020Overview of QA - Part 1PDFPart 1, Part 2
0210 November 2020Overview of QA - Part 2, Seminar logisticsPDFPart 1, Part 2
-01 December 2020Block seminar day 1  
-08 December 2020Block seminar day 2  
-15 December 2020Block seminar day 3  

Reading material 

  1. Zhao, Chen, Chenyan Xiong, Xin Qian, and Jordan Boyd-Graber. "Complex Factoid Question Answering with a Free-Text Knowledge Graph." In Proceedings of The Web Conference 2020, pp. 1205-1216. 2020.
  2. Asai, Akari, Kazuma Hashimoto, Hannaneh Hajishirzi, Richard Socher, and Caiming Xiong. "Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering." In International Conference on Learning Representations. 2019.
  3. Saha, Amrita, Vardaan Pahuja, Mitesh M. Khapra, Karthik Sankaranarayanan, and Sarath Chandar. "Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph." In AAAI. 2018.
  4. Guo, Daya, Duyu Tang, Nan Duan, Ming Zhou, and Jian Yin. "Dialog-to-action: Conversational question answering over a large-scale knowledge base." In Advances in Neural Information Processing Systems, pp. 2942-2951. 2018.
  5. Sawant, Uma, Saurabh Garg, Soumen Chakrabarti, and Ganesh Ramakrishnan. "Neural architecture for question answering using a knowledge graph and web corpus." Information Retrieval Journal 22, no. 3-4 (2019): 324-349.
  6. Bhutani, Nikita, and H. V. Jagadish. "Online Schemaless Querying of Heterogeneous Open Knowledge Bases." In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 699-708. 2019.
  7. Hua, Yuncheng, Yuan-Fang Li, Gholamreza Haffari, Guilin Qi, and Tongtong Wu. "Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learning." In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pp. 5827-5837. 2020.
  8. Qiu, Yunqi, Kun Zhang, Yuanzhuo Wang, Xiaolong Jin, Long Bai, Saiping Guan, and Xueqi Cheng. "Hierarchical Query Graph Generation for Complex Question Answering over Knowledge Graph." In Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp. 1285-1294. 2020.
  9. Zhang, Xinbo, Lei Zou, and Sen Hu. "An Interactive Mechanism to Improve Question Answering Systems via Feedback." In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 1381-1390. 2019.
  10. Wu, Zhiyong, Ben Kao, Tien-Hsuan Wu, Pengcheng Yin, and Qun Liu. "PERQ: Predicting, Explaining, and Rectifying Failed Questions in KB-QA Systems." In Proceedings of the 13th International Conference on Web Search and Data Mining, pp. 663-671. 2020.
  11. Khashabi, Daniel, Tushar Khot, Ashish Sabharwal, and Dan Roth. "Question answering as global reasoning over semantic abstractions." In AAAI. 2018.
  12. Khashabi, Daniel, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, and Dan Roth. "Question answering via integer programming over semi-structured knowledge." In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, pp. 1145-1152. 2016.
  13. Hu, Sen, Lei Zou, and Xinbo Zhang. "A state-transition framework to answer complex questions over knowledge base." In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 2098-2108. 2018.
  14. Ding, Jiwei, Wei Hu, Qixin Xu, and Yuzhong Qu. "Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question Answering." In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 2614-2622. 2019.
  15. Talmor, Alon, and Jonathan Berant. "The Web as a Knowledge-Base for Answering Complex Questions." In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pp. 641-651. 2018.
  16. Zhang, Haoyu, Jingjing Cai, Jianjun Xu, and Ji Wang. "Complex question decomposition for semantic parsing." In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pp. 4477-4486. 2019.
  17. Fader, Anthony, Luke Zettlemoyer, and Oren Etzioni. "Open question answering over curated and extracted knowledge bases." In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 1156-1165. 2014.
  18. Sun, Haitian, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, and William Cohen. "Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text." In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 4231-4242. 2018.
  19. Bhutani, Nikita, Xinyi Zheng, and H. V. Jagadish. "Learning to answer complex questions over knowledge bases with query composition." In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 739-748. 2019.
  20. Yin, Pengcheng, Nan Duan, Ben Kao, Junwei Bao, and Ming Zhou. "Answering questions with complex semantic constraints on open knowledge bases." In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, pp. 1301-1310. 2015.
  21. Wang, Jian, Junhao Liu, Wei Bi, Xiaojiang Liu, Kejing He, Ruifeng Xu, and Min Yang. "Improving Knowledge-Aware Dialogue Generation via Knowledge Base Question Answering." In AAAI, pp. 9169-9176. 2020.
  22. Xu, Jingjing, Yuechen Wang, Duyu Tang, Nan Duan, Pengcheng Yang, Qi Zeng, Ming Zhou, and S. U. N. Xu. "Asking Clarification Questions in Knowledge-Based Question Answering." In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 1618-1629. 2019.
  23. Yahya, Mohamed, Klaus Berberich, Shady Elbassuoni, Maya Ramanath, Volker Tresp, and Gerhard Weikum. "Natural language questions for the web of data." In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 379-390. 2012.
  24. Yahya, Mohamed, Denilson Barbosa, Klaus Berberich, Qiuyue Wang, and Gerhard Weikum. "Relationship queries on extended knowledge graphs." In Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, pp. 605-614. 2016.
  25. Qiu, Yunqi, Yuanzhuo Wang, Xiaolong Jin, and Kun Zhang. "Stepwise Reasoning for Multi-Relation Question Answering over Knowledge Graph with Weak Supervision." In Proceedings of the 13th International Conference on Web Search and Data Mining, pp. 474-482. 2020.
  26. Jhamtani, Harsh, and Peter Clark. "Learning to Explain: Datasets and Models for Identifying Valid Reasoning Chains in Multihop Question-Answering." In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pp. 137-150. 2020.
  27. Dhingra, Bhuwan, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov, and William W. Cohen. "Differentiable Reasoning over a Virtual Knowledge Base." In International Conference on Learning Representations. 2019.
  28. Cohen, William W., Haitian Sun, R. Alex Hofer, and Matthew Siegler. "Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base." In International Conference on Learning Representations. 2019.
  29. Cui, Wanyun, Yanghua Xiao, Haixun Wang, Yangqiu Song, Seung-won Hwang, and Wei Wang. "KBQA: learning question answering over QA corpora and knowledge bases." Proceedings of the VLDB Endowment 10, no. 5 (2017): 565-576.
  30. Sun, Yawei, Lingling Zhang, Gong Cheng, and Yuzhong Qu. "SPARQA: Skeleton-Based Semantic Parsing for Complex Questions over Knowledge Bases." In AAAI, pp. 8952-8959. 2020.
  31. Li, Guoliang, Beng Chin Ooi, Jianhua Feng, Jianyong Wang, and Lizhu Zhou. "EASE: an effective 3-in-1 keyword search method for unstructured, semi-structured and structured data." In Proceedings of the 2008 ACM SIGMOD international conference on Management of data, pp. 903-914. 2008.
  32. Shi, Yuxuan, Gong Cheng, and Evgeny Kharlamov. "Keyword Search over Knowledge Graphs via Static and Dynamic Hub Labelings." In Proceedings of The Web Conference 2020, pp. 235-245. 2020.