SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documen
model 主要貢獻 提出了一種基於遞歸神經網絡RNN的抽取式摘要的序列模型 可解釋強-可視化‘ 對抽取模型進行抽象化的訓練，該模型可以單獨對人工生成的參考摘要進行訓練，從而消除了句子級抽取’標籤的需求。 一種基於兩層RNN的序列分類器：底層在每個句子中的word level上工作，而頂層運行在sentence level 。雙指向箭頭表示雙向RNN。 1和0的頂層是基於sigmoid的分類層，它
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相關文章
- 1. Taming Recurrent Neural Networks for Better Summarization
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