Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment

• URL: http://arxiv.org/abs/2307.03319v1
• Date: Thu, 6 Jul 2023 22:21:42 GMT
• Title: Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment
• Authors: Roni Rabin, Alexandre Djerbetian, Roee Engelberg, Lidan Hackmon, Gal Elidan, Reut Tsarfaty, Amir Globerson
• Abstract summary: We focus on the problem of generating such gap-focused questions (GFQs) automatically. We define the task, highlight key desired aspects of a good GFQ, and propose a model that satisfies these.
• Score: 75.59538732476346
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Human communication often involves information gaps between the interlocutors. For example, in an educational dialogue, a student often provides an answer that is incomplete, and there is a gap between this answer and the perfect one expected by the teacher. Successful dialogue then hinges on the teacher asking about this gap in an effective manner, thus creating a rich and interactive educational experience. We focus on the problem of generating such gap-focused questions (GFQs) automatically. We define the task, highlight key desired aspects of a good GFQ, and propose a model that satisfies these. Finally, we provide an evaluation by human annotators of our generated questions compared against human generated ones, demonstrating competitive performance.

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