A Systematic Review of Reproducibility Research in Natural Language Processing

Anya Belz, Anastasia Shimorina, Shubham Agarwal, Ehud Reiter

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

30 Citations (Scopus)

Abstract

Against the background of what has been termed a reproducibility crisis in science, the NLP field is becoming increasingly interested in, and conscientious about, the reproducibility of its results. The past few years have seen an impressive range of new initiatives, events and active research in the area. However, the field is far from reaching a consensus about how reproducibility should be defined, measured and addressed, with diversity of views currently increasing rather than converging. With this focused contribution, we aim to provide a wide-angle, and as near as possible complete, snapshot of current work on reproducibility in NLP, delineating differences and similarities, and providing pointers to common denominators.
Original languageEnglish
Title of host publicationProceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics
Subtitle of host publicationMain Volume
PublisherACL Anthology
Pages381-393
Number of pages13
ISBN (Electronic)978-1-954085-02-2
DOIs
Publication statusPublished - 23 Apr 2021
EventEACL 2021 : 16th Conference of the European Chapter of the Association for Computational Linguistics - Virtual event
Duration: 19 Apr 202123 Apr 2021
https://2021.eacl.org/

Conference

ConferenceEACL 2021
Abbreviated titleEACL21
Period19/04/2123/04/21
Internet address

Bibliographical note

Acknowledgments
We thank our reviewers for their valuable feedback. Shubham Agarwal’s PhD fees are supported by Adeptmind Inc., Toronto, Canada.

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