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A Co-Matching Model for Multi-choice Reading Comprehension

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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.

Shuohang Wang, Mo Yu, Shiyu Chang, Jing Jiang• 2018

Related benchmarks

TaskDatasetResultRank
Machine Reading ComprehensionRACE (test)
RACE Accuracy (Medium)55.8
111
Machine Reading ComprehensionRACE
RACE Overall Accuracy50.4
38
Multiple-choice reading comprehensionViMMRC 2.0
Accuracy41.21
21
Multiple-choice reading comprehensionViRCSoSciD
Accuracy34.76
12
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