(QA)²: Question Answering with Questionable Assumptions

Naturally occurring information-seeking questions often contain questionable assumptions-assumptions that are false or unverifiable. Questions containing questionable assumptions are challenging because they require a distinct answer strategy that deviates from typical answers for information-seeking questions. For instance, the question When did Marie Curie discover Uranium? cannot be answered as a typical when question without addressing the false assumption Marie Curie discovered Uranium. In this work, we propose (QA) 2 (Question Answering with Questionable Assumptions), an open-domain evaluation dataset consisting of naturally occurring search engine queries that may or may not contain questionable assumptions. To be successful on (QA) 2 , systems must be able to detect questionable assumptions and also be able to produce adequate responses for both typical information-seeking questions and ones with questionable assumptions. Through human rater acceptability on end-to-end QA with (QA) 2 , we find that current models do struggle with handling questionable assumptions, leaving substantial headroom for progress. * Equal contribution, corresponding authors ∆ Work partly done at NYU before joining BU. δ Work done at NYU before joining Amazon. 1 We use the term questionable assumptions instead of presupposition failure to capture failures of both true presup-