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Abstract: Inspired by how humans summarize long documents, we propose an accurate and fast summarization model that first selects salient sentences and then rewrites them abstractively (i.e., compresses and paraphrases) to generate a concise overall summary. We use a novel sentence-level policy gradient method to bridge the non-differentiable computation between these two neural networks in a hierarchical way, while maintaining language fluency. Empirically, we achieve the new state-of-the-art on all metrics (including human evaluation) on the CNN/Daily Mail dataset, as well as significantly higher abstractiveness scores. Moreover, by first operating at the sentence-level and then the word-level, we enable parallel decoding of our neural generative model that results in substantially faster (10-20x) inference speed as well as 4x faster training convergence than previous long-paragraph encoder-decoder models. We also demonstrate the generalization of our model on the test-only DUC-2002 dataset, where we achieve higher scores than a state-of-the-art model.
Comments: ACL 2018 (17 pages)
Jeans Blue Spykar Rise Mens Narrow Rover Low Fit Fit dt9RRuDS18 Subjects: Computation and Language (cs.CL) ; Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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[cs.CL]
  (or arXiv:1805.11080v1 [cs.CL] for this version)

Submission history

From: Yen-Chun Chen [ view email ]
[v1] Mon, 28 May 2018 17:49:10 GMT (552kb,D)

Description

Spykar Mens Blue Narrow Fit Low Rise Jeans (Rover Fit)
Brand
Spykar
Product Code
APPSPYKAR-MENS-SETU2010437355E477
Color
Blue
Size
36
Material
Cotton
Occasion
Casual
Rise
Low Rise
Pattern
Solid
Fit
Narrow
Gender
Men
Set Contents
1
Wash Care
Hand Wash
Article Identifier Type
8901241656150
Article Identification Value
Ean Code
Style Code
RO-02AG-17