{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-feasibility-study-of-answer-unaware-2","title":"A Feasibility Study of Answer-Unaware Question Generation for Education","arxiv_id":null,"date":"2022-05-01","proceeding":"Findings (ACL) 2022 5","authors":["Liam Dugan","Eleni Miltsakaki","Shriyash Upadhyay","Etan Ginsberg","Hannah Gonzalez","DaHyeon Choi","Chuning Yuan","Chris Callison-Burch"],"abstract":"We conduct a feasibility study into the applicability of answer-unaware question generation models to textbook passages. We show that a significant portion of errors in such systems arise from asking irrelevant or un-interpretable questions and that such errors can be ameliorated by providing summarized input. We find that giving these models human-written summaries instead of the original text results in a significant increase in acceptability of generated questions (33% \\rightarrow 83%) as determined by expert annotators. We also find that, in the absence of human-written summaries, automatic summarization can serve as a good middle ground.","url_abs":"https://aclanthology.org/2022.findings-acl.151","url_pdf":"https://aclanthology.org/2022.findings-acl.151.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-feasibility-study-of-answer-unaware-2","repo_url":"https://github.com/liamdugan/summary-qg","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"question-generation","task_name":"Question Generation"},{"task_slug":"question-generation","task_name":"Question-Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}