Fact-based Content Weighting for Evaluating Abstractive Summarisation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10424511" target="_blank" >RIV/00216208:11320/20:10424511 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/2020.acl-main.455/" target="_blank" >https://www.aclweb.org/anthology/2020.acl-main.455/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2020.acl-main.455" target="_blank" >10.18653/v1/2020.acl-main.455</a>
Alternative languages
Result language
angličtina
Original language name
Fact-based Content Weighting for Evaluating Abstractive Summarisation
Original language description
Abstractive summarisation is notoriously hard to evaluate since standard word-overlap-based metrics are insufficient. We introduce a new evaluation metric which is based on fact-level content weighting, i.e. relating the facts of the document to the facts of the summary. We follow the assumption that a good summary will reflect all relevant facts, i.e. the ones present in the ground truth (human-generated refer- ence summary). We confirm this hypothe- sis by showing that our weightings are highly correlated to human perception and compare favourably to the recent manual highlight- based metric of Hardy et al. (2019).
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
ISBN
978-1-952148-25-5
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
5071-5081
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Online
Event date
Jul 5, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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