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Improving Neural Abstractive Document Summarization with Structural Regularization

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Figure

Figure 1: Comparison of sentence-level attention distribu-tem and (e) is for our system.sentence of the input and output, respectively
Figure 2:Our hierarchical encoder-decoder model withstructural regularization for abstractive document summa-rization.
Table 3: Comparison results w.r.t different length of refer-ence summary. < 100 indicates the reference summary hasless than 100 words (occupy 94.47% of test set).
Table 5: Results of adding different components of ourmethod in terms of ROUGE-1, ROUGE-2, ROUGE-L, str-Com (Equation 1) and strCov (Equation 2) scores.
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