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 language | English |
---|---|
Title of host publication | Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics |
Subtitle of host publication | Main Volume |
Publisher | ACL Anthology |
Pages | 381-393 |
Number of pages | 13 |
ISBN (Electronic) | 978-1-954085-02-2 |
DOIs | |
Publication status | Published - 23 Apr 2021 |
Event | EACL 2021 : 16th Conference of the European Chapter of the Association for Computational Linguistics - Virtual event Duration: 19 Apr 2021 → 23 Apr 2021 https://2021.eacl.org/ |
Conference
Conference | EACL 2021 |
---|---|
Abbreviated title | EACL21 |
Period | 19/04/21 → 23/04/21 |
Internet address |
Bibliographical note
AcknowledgmentsWe thank our reviewers for their valuable feedback. Shubham Agarwal’s PhD fees are supported by Adeptmind Inc., Toronto, Canada.