A Co-Matching Model for Multi-choice Reading Comprehension

June 11, 2018 ยท Declared Dead ยท ๐Ÿ› Annual Meeting of the Association for Computational Linguistics

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Authors Shuohang Wang, Mo Yu, Shiyu Chang, Jing Jiang arXiv ID 1806.04068 Category cs.CL: Computation & Language Citations 95 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 4 months ago
Abstract
Multi-choice reading comprehension is a challenging task, which involves the matching between a passage and a question-answer pair. This paper proposes a new co-matching approach to this problem, which jointly models whether a passage can match both a question and a candidate answer. Experimental results on the RACE dataset demonstrate that our approach achieves state-of-the-art performance.
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