SubmissionNumber#=%=#7
FinalPaperTitle#=%=#Extract, Select and Rewrite: A Modular Sentence Summarization Method
ShortPaperTitle#=%=#
NumberOfPages#=%=#8
CopyrightSigned#=%=#Shuo Guan
JobTitle#==#
Organization#==#
Abstract#==#A modular approach has the advantage of being compositional and controllable, comparing to most end-to-end models.
  In this paper we propose Extract-Select-Rewrite (ESR), a three-phase abstractive sentence summarization method.
  We decompose summarization into three stages:
  (i) knowledge extraction, where we extract relation triples from the text using off-the-shelf tools;
  (ii) content selection, where a subset of triples are selected;
  and (iii) rewriting, where the selected triple are realized into natural language.
  Our results demonstrates that ESR is competitive with the best end-to-end models while being more faithful. %than these baseline models.
  Being modular, ESR's modules can be trained on separate data which is beneficial in low-resource settings and enhancing the style controllability on text generation.
Author{1}{Firstname}#=%=#Shuo
Author{1}{Lastname}#=%=#Guan
Author{1}{Username}#=%=#seanguan
Author{1}{Email}#=%=#shuo.guan@cs.nyu.edu
Author{1}{Affiliation}#=%=#UBS
Author{2}{Firstname}#=%=#Vishakh
Author{2}{Lastname}#=%=#Padmakumar
Author{2}{Username}#=%=#vishakhpk
Author{2}{Email}#=%=#vp1271@nyu.edu
Author{2}{Affiliation}#=%=#New York University

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