Deduplicating Training Data Makes Language Models Better

Lee, Katherine; Ippolito, Daphne; Nystrom, Andrew; Zhang, Chiyuan; Eck, Douglas; Callison-Burch, Chris; Carlini, Nicholas

doi:10.18653/v1/2022.acl-long.577

articleProceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)Jan 1, 2022HYBRID OA

Deduplicating Training Data Makes Language Models Better

KLKatherine Lee DIDaphne Ippolito ANAndrew Nystrom CZChiyuan Zhang DEDouglas Eck

Brain (Germany) · Google (United States) · +1 more institution

Indexed incrossref

Abstract

Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2022.

Citation impact

252

total citations

FWCI: 23.47
Percentile: 100%
References: 60

Citations per year

Authors

KL
Katherine Lee
Brain (Germany), Google (United States)
DI
Daphne IppolitoCorresponding
California University of Pennsylvania, Google (United States), Brain (Germany)
AN
Andrew Nystrom
Brain (Germany), Google (United States)
CZ
Chiyuan Zhang
Google (United States), Brain (Germany)
DE
Douglas Eck
Brain (Germany), Google (United States)

Topics & keywords

Topics

Topic Modeling100%
Natural Language Processing Techniques100%
Data Quality and Management99%

Keywords

Zhàng
Computer science
Volume (thermodynamics)
Computational linguistics
Natural language processing
Artificial intelligence
Linguistics
Library science

UN Sustainable Development Goals

Quality Education

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