Reinforced Mnemonic Reader for Machine Reading Comprehension

Minghao HuYuxing PengZhen HuangXipeng QiuFuru WeiMing Zhou

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In this paper, we introduce the Reinforced Mnemonic Reader for machine reading comprehension tasks, which enhances previous attentive readers in two aspects. First, a reattention mechanism is proposed to refine current attentions by directly accessing to past attentions that are temporally memorized in a multi-round alignment architecture, so as to avoid the problems of attention redundancy and attention deficiency... (read more)

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