Program Chairs’ Report on Peer Review at ACL 2023

Anna Rogers, Marzena Karpinska, Jordan Boyd-Graber, Naoaki Okazaki


Abstract
We present a summary of the efforts to improve conference peer review that were implemented at ACL’23. This includes work with the goal of improving review quality, clearer workflow and decision support for the area chairs, as well as our efforts to improve paper-reviewer matching for various kinds of non- mainstream NLP work, and improve the overall incentives for all participants of the peer review process. We present analysis of the factors affecting peer review, identify the most problematic issues that the authors complained about, and provide suggestions for the future chairs. We hope that publishing such reports would (a) improve transparency in decision-making, (b) help the people new to the field to understand how the *ACL conferences work, (c) provide useful data for the future chairs and workshop organizers, and also academic work on peer review, and (d) provide useful context for the final program, as a source of information for meta-research on the structure and trajectory of the field of NLP.
Anthology ID:
2023.acl-long.911
Volume:
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
xl–lxxv
Language:
URL:
https://aclanthology.org/2023.acl-long.report
DOI:
Bibkey:
Cite (ACL):
Anna Rogers, Marzena Karpinska, Jordan Boyd-Graber, and Naoaki Okazaki. 2023. Program Chairs’ Report on Peer Review at ACL 2023. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), page xl–lxxv, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Program Chairs’ Report on Peer Review at ACL 2023 (Rogers et al., ACL 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.acl-long.report.pdf