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Creators/Authors contains: "Maharshi Gor, Kellie Webster"

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  1. (, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing)
    The goal of question answering (QA) is to answer any question. However, major QA datasets have skewed distributions over gender, profession, and nationality. Despite that skew, model accuracy analysis reveals little evidence that accuracy is lower for people based on gender or nationality; instead, there is more variation on professions (question topic). But QA’s lack of representation could itself hide evidence of bias, necessitating QA datasets that better represent global diversity. 
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