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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)
England Shirt White Peter rfPkbs Subjects: Computation and Language (cs.CL) ; Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
Peter White Shirt England UvFUvU4SiB Cite as: arXiv:1805.11080 [cs.CL]
  (or Mens Denim Blinder Shoes Navy Blue Velcro Casual xn7hJiHRZF
[cs.CL]
for this version)

Submission history

From: Yen-Chun Chen [ Linen Mens Cotton For Solemio Shirt bk83u
]
[v1] Mon, 28 May 2018 17:49:10 GMT (552kb,D)

Description

Lend a stylish twist to your weekend roster with this printed white shirt from Peter England Jeans. Tailored for a super slim fit;this shirt is crafted from cotton. Wear it with denims and sneakers to finish your look.
Brand
Peter England
Product Code
APPPETER-ENGLANADIT50996691F8AC5
Color
White
Size
42
Material
Cotton
Pattern
Solid
Sleeve
Full Sleeves
Neck Type
Classic Collar
Fit
Super Slim
Gender
Men
Collar Type
Spread Collar
Set Contents
1
Wash Care
Machine Wash
Article Identifier Type
EAN CODE
Article Identification Value
8907827400155
Style Code
JSF318009392