Always private
DuckDuckGo never tracks your searches.
Learn More
You can hide this reminder in Search Settings
All regions
Argentina
Australia
Austria
Belgium (fr)
Belgium (nl)
Brazil
Bulgaria
Canada (en)
Canada (fr)
Catalonia
Chile
China
Colombia
Croatia
Czech Republic
Denmark
Estonia
Finland
France
Germany
Greece
Hong Kong
Hungary
Iceland
India (en)
Indonesia (en)
Ireland
Israel (en)
Italy
Japan
Korea
Latvia
Lithuania
Malaysia (en)
Mexico
Netherlands
New Zealand
Norway
Pakistan (en)
Peru
Philippines (en)
Poland
Portugal
Romania
Russia
Saudi Arabia
Singapore
Slovakia
Slovenia
South Africa
Spain (ca)
Spain (es)
Sweden
Switzerland (de)
Switzerland (fr)
Taiwan
Thailand (en)
Turkey
Ukraine
United Kingdom
US (English)
US (Spanish)
Vietnam (en)
Safe search: moderate
Strict
Moderate
Off
Any time
Any time
Past day
Past week
Past month
Past year
  1. aclanthology.org

    4 days agoIn this paper we conceptualize extractive summarization as a sentence ranking task and propose a novel training algorithm which globally optimizes the ROUGE evaluation metric through a reinforcement learning objective. ... , title = "Ranking Sentences for Extractive Summarization with Reinforcement Learning", author = "Narayan, Shashi and Cohen ...
    Author:Shashi Narayan, Shay B. Cohen, Mirella LapataPublished:2018
  2. homepages.inf.ed.ac.uk

    Figure 1: Extractive summarization model with reinforcement learning: a hierarchical encoder-decoder model ranks sentences for their extract-worthiness and a candidate summary is assembled from the top ranked sentences; the REWARD generator compares the candidate against the gold summary to give a reward which is used in the
  3. Download PDF Abstract: Single document summarization is the task of producing a shorter version of a document while preserving its principal information content. In this paper we conceptualize extractive summarization as a sentence ranking task and propose a novel training algorithm which globally optimizes the ROUGE evaluation metric through a reinforcement learning objective.
    Author:Shashi Narayan, Shay B. Cohen, Mirella LapataPublished:2018
  4. researchgate.net

    The most relevant ones to our work are extractive summarization methods, which model the summarization as classification [29,21] and reinforcement learning problem [23]. There are also abstractive ...
  5. researchgate.net

    Despite the first works on Reinforcement Learning being intended to perform abstractive summarization by Paulus et al. [28], recently these strategies have been widely used for extractive text ...
  6. Ranking Sentences for Extractive Summarization with Reinforcement Learning Shashi Narayan Shay B. Cohen Mirella Lapata ILCC, School of Informatics, Universityof Edinburgh 10 Crichton Street, Edinburgh, EH8 9AB, UK shashi.narayan@ed.ac.uk {scohen,mlap}@inf.ed.ac.uk Abstract Single document summarization is the task of producing a shorter version ...
  7. sigir-ecom.github.io

    sentences. We use Extractive Summarization to achieve this. Our work is based on [16] which treats summarization task as a ranking problem and training is done by optimizing combination of ROUGE metric and cross entropy using reinforcement learning (described in 3.2). ROUGE stands for Recall-Oriented Understudy for Gisting Evaluation.
  8. semanticscholar.org

    This paper conceptualize extractive summarization as a sentence ranking task and proposes a novel training algorithm which globally optimizes the ROUGE evaluation metric through a reinforcement learning objective. Single document summarization is the task of producing a shorter version of a document while preserving its principal information content. In this paper we conceptualize extractive ...
  9. ar5iv.labs.arxiv.org

    Reinforcement learning Sutton and Barto has been proposed as a way of training sequence-to-sequence generation models in order to directly optimize the metric used at test time, e.g., BLEU or ROUGE Ranzato et al. . We adapt reinforcement learning to our formulation of extractive summarization to rank sentences for summary generation.
  10. The paper Ranking Sentences for Extractive Summarization with Reinforcement Learning proposes an Extractive Summarization Model with Reinforcement Learning — a model which ranks sentences based ...

    Can’t find what you’re looking for?

    Help us improve DuckDuckGo searches with your feedback

Custom date rangeX