Train Hard, Finetune Easy: Multilingual Denoising for RDF-to-Text Generation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10424456" target="_blank" >RIV/00216208:11320/20:10424456 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/2020.webnlg-1.20/" target="_blank" >https://www.aclweb.org/anthology/2020.webnlg-1.20/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Train Hard, Finetune Easy: Multilingual Denoising for RDF-to-Text Generation
Original language description
We describe our system for the RDF-to-text generation task of the WebNLG Challenge 2020. We base our approach on the mBART model, which is pre-trained for multilingual denoising. This allows us to use a simple, identical, end-to-end setup for both English and Russian. Requiring minimal task or language-specific effort, our model placed in the first third of the leaderboard for English and first or second for Russian on automatic metrics, and it made it into the best or second-best system cluster on human evaluation.
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
S - Specificky vyzkum na vysokych skolach<br>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 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+)
ISBN
978-1-952148-59-0
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
171-176
Publisher name
Association for Computational Linguistics
Place of publication
Stroudsburg, PA, USA
Event location
Online
Event date
Dec 18, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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