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Paper Abstract Writing through Editing Mechanism

机译:通过编辑机制进行论文摘要写作

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摘要

We present a paper abstract writing system based on an attentive neural sequence-to-sequence model that can take a title as input and automatically generate an abstract. We design a novel Writing-editing Network that can attend to both the title and the previously generated abstract drafts and then iteratively revise and polish the abstract. With two series of Turing tests, where the human judges are asked to distinguish the system-generated abstracts from human-written ones, our system passes Turing tests by junior domain experts at a rate up to 30% and by nonexpert at a rate up to 80%.
机译:我们提出了一种基于注意力神经序列到序列模型的论文摘要写作系统,该模型可以将标题作为输入并自动生成摘要。我们设计了一个新颖的写作编辑网络,该网络可以同时参与标题和先前生成的摘要草稿,然后迭代修改和修饰摘要。通过两个系列的图灵测试,要求人类法官将系统生成的摘要与人工编写的摘要区分开,我们的系统通过初中领域专家的图灵测试以不超过30%的比率通过非专业人士以不超过30%的比率通过80%。

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