Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering

Hao Cheng, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering. In Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel R. Tetreault, editors, Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020. pages 5657-5667, Association for Computational Linguistics, 2020. [doi]

Abstract

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