mlsanityData to 14 Oct 2026

Interactive Question Answering Systems: Literature Review

arXiv 2209.01621 ↗First posted 4 Sep 2022cs.CL cs.AI cs.HCcited by 7

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Abstract (arXiv)

Question answering systems are recognized as popular and frequently effective means of information seeking on the web. In such systems, information seekers can receive a concise response to their query by presenting their questions in natural language. Interactive question answering is a recently proposed and increasingly popular solution that resides at the intersection of question answering and dialogue systems. On the one hand, the user can ask questions in normal language and locate the actual response to her inquiry; on the other hand, the system can prolong the question-answering session into a dialogue if there are multiple probable replies, very few, or ambiguities in the initial request. By permitting the user to ask more questions, interactive question answering enables users to dynamically interact with the system and receive more precise results. This survey offers a detailed overview of the interactive question-answering methods that are prevalent in current literature. It begins by explaining the foundational principles of question-answering systems, hence defining new notations and taxonomies to combine all identified works inside a unified framework. The reviewed published work on interactive question-answering systems is then presented and examined in terms of its proposed methodology, evaluation approaches, and dataset/application domain. We also describe trends surrounding specific tasks and issues raised by the community, so shedding light on the future interests of scholars. Our work is further supported by a GitHub page with a synthesis of all the major topics covered in this literature study. https://sisinflab.github.io/interactive-question-answering-systems-survey/

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 83 of its 199 references that are in the map. First posted on arXiv 4 Sep 2022.

Builds on

83 of 199 references.

References · 83

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38 more
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  2. 2018QuAC : Question Answering in Contextcited by 381
  3. 2017TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answeringcited by 378
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Citing papers per year: 2023: 2; 2024: 2; 2025: 3.

7 papers.