@inproceedings{heo-etal-2026-drives,
title = "What Drives Paper Acceptance? A Process-Centric Analysis of Modern Peer Review",
author = "Heo, Inbum and
Pyeon, Goun and
Ahn, Hyungjin and
Jung, Sangkeun",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.emnlp-main.1123/",
pages = "25711--25731",
ISBN = "979-8-89176-459-0",
abstract = "Peer review is the primary mechanism for evaluating scientific contributions, yet prior studies have mostly examined paper features or external metadata in isolation. The emergence of open platforms such as OpenReview has transformed peer review into a transparent and interactive process, recording not only scores and comments but also rebuttals, reviewer{--}author exchanges, and meta-reviewer decisions. In this paper, we present a large-scale empirical study of ICLR 2017{--}2025, encompassing over 28,000 submissions, integrating four dimensions: paper structure and language quality, submission strategies and external metadata, author{--}reviewer interaction dynamics, and reviewer disagreement patterns. Our results show that factors beyond scientific novelty significantly shape acceptance outcomes. In particular, the rebuttal stage emerges as a decisive phase: timely, substantive author{--}reviewer communication strongly increases acceptance likelihood, often outweighing initial reviewer skepticism. Clearer writing, earlier submission, and effective disagreement resolution also correlate with higher acceptance probabilities. Based on these findings, we propose data-driven guidelines for authors, reviewers, and meta-reviewers to enhance transparency and fairness in peer review."
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<abstract>Peer review is the primary mechanism for evaluating scientific contributions, yet prior studies have mostly examined paper features or external metadata in isolation. The emergence of open platforms such as OpenReview has transformed peer review into a transparent and interactive process, recording not only scores and comments but also rebuttals, reviewer–author exchanges, and meta-reviewer decisions. In this paper, we present a large-scale empirical study of ICLR 2017–2025, encompassing over 28,000 submissions, integrating four dimensions: paper structure and language quality, submission strategies and external metadata, author–reviewer interaction dynamics, and reviewer disagreement patterns. Our results show that factors beyond scientific novelty significantly shape acceptance outcomes. In particular, the rebuttal stage emerges as a decisive phase: timely, substantive author–reviewer communication strongly increases acceptance likelihood, often outweighing initial reviewer skepticism. Clearer writing, earlier submission, and effective disagreement resolution also correlate with higher acceptance probabilities. Based on these findings, we propose data-driven guidelines for authors, reviewers, and meta-reviewers to enhance transparency and fairness in peer review.</abstract>
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%0 Conference Proceedings
%T What Drives Paper Acceptance? A Process-Centric Analysis of Modern Peer Review
%A Heo, Inbum
%A Pyeon, Goun
%A Ahn, Hyungjin
%A Jung, Sangkeun
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-459-0
%F heo-etal-2026-drives
%X Peer review is the primary mechanism for evaluating scientific contributions, yet prior studies have mostly examined paper features or external metadata in isolation. The emergence of open platforms such as OpenReview has transformed peer review into a transparent and interactive process, recording not only scores and comments but also rebuttals, reviewer–author exchanges, and meta-reviewer decisions. In this paper, we present a large-scale empirical study of ICLR 2017–2025, encompassing over 28,000 submissions, integrating four dimensions: paper structure and language quality, submission strategies and external metadata, author–reviewer interaction dynamics, and reviewer disagreement patterns. Our results show that factors beyond scientific novelty significantly shape acceptance outcomes. In particular, the rebuttal stage emerges as a decisive phase: timely, substantive author–reviewer communication strongly increases acceptance likelihood, often outweighing initial reviewer skepticism. Clearer writing, earlier submission, and effective disagreement resolution also correlate with higher acceptance probabilities. Based on these findings, we propose data-driven guidelines for authors, reviewers, and meta-reviewers to enhance transparency and fairness in peer review.
%U https://aclanthology.org/2026.emnlp-main.1123/
%P 25711-25731
Markdown (Informal)
[What Drives Paper Acceptance? A Process-Centric Analysis of Modern Peer Review](https://aclanthology.org/2026.emnlp-main.1123/) (Heo et al., EMNLP 2026)
ACL