@inproceedings{aubert-beduchaud-etal-2026-towards,
title = "Towards Reliable Paper Contributions Annotation in the {ACL} Rolling Review",
author = "Aubert-B{\'e}duchaud, Julien and
Boudin, Florian and
Aizawa, Akiko and
Daille, Beatrice and
Dufour, Richard",
editor = "Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David",
booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
month = jul,
year = "2026",
address = "San Diego, California, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.findings-acl.178/",
pages = "3636--3653",
ISBN = "979-8-89176-395-1",
abstract = "With the rapid growth of scientific publications, researchers struggle to efficiently assess the relevance of numerous papers. Identifying the types of contributions an article makes can help readers quickly grasp its significance. The ACL Rolling Review (ARR) introduced a typology requiring authors to specify their contributions to improve review quality and fairness. However, the current typology lacks clear definitions and guidance, leading to inconsistent labeling and raising concerns about its reliability.Our re-annotation campaign reveals substantial disagreement between authors and domain experts. Moreover, the predictions of large language models (LLMs), when compared with expert annotations, tend to be close to those provided by the authors. These findings suggest a potential path toward better annotation reliability within the ARR process."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="aubert-beduchaud-etal-2026-towards">
<titleInfo>
<title>Towards Reliable Paper Contributions Annotation in the ACL Rolling Review</title>
</titleInfo>
<name type="personal">
<namePart type="given">Julien</namePart>
<namePart type="family">Aubert-Béduchaud</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Florian</namePart>
<namePart type="family">Boudin</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Akiko</namePart>
<namePart type="family">Aizawa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Beatrice</namePart>
<namePart type="family">Daille</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Richard</namePart>
<namePart type="family">Dufour</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Findings of the Association for Computational Linguistics: ACL 2026</title>
</titleInfo>
<name type="personal">
<namePart type="given">Maria</namePart>
<namePart type="family">Liakata</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Viviane</namePart>
<namePart type="given">P</namePart>
<namePart type="family">Moreira</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jiajun</namePart>
<namePart type="family">Zhang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">David</namePart>
<namePart type="family">Jurgens</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">San Diego, California, United States</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-395-1</identifier>
</relatedItem>
<abstract>With the rapid growth of scientific publications, researchers struggle to efficiently assess the relevance of numerous papers. Identifying the types of contributions an article makes can help readers quickly grasp its significance. The ACL Rolling Review (ARR) introduced a typology requiring authors to specify their contributions to improve review quality and fairness. However, the current typology lacks clear definitions and guidance, leading to inconsistent labeling and raising concerns about its reliability.Our re-annotation campaign reveals substantial disagreement between authors and domain experts. Moreover, the predictions of large language models (LLMs), when compared with expert annotations, tend to be close to those provided by the authors. These findings suggest a potential path toward better annotation reliability within the ARR process.</abstract>
<identifier type="citekey">aubert-beduchaud-etal-2026-towards</identifier>
<location>
<url>https://aclanthology.org/2026.findings-acl.178/</url>
</location>
<part>
<date>2026-07</date>
<extent unit="page">
<start>3636</start>
<end>3653</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Towards Reliable Paper Contributions Annotation in the ACL Rolling Review
%A Aubert-Béduchaud, Julien
%A Boudin, Florian
%A Aizawa, Akiko
%A Daille, Beatrice
%A Dufour, Richard
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Findings of the Association for Computational Linguistics: ACL 2026
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-395-1
%F aubert-beduchaud-etal-2026-towards
%X With the rapid growth of scientific publications, researchers struggle to efficiently assess the relevance of numerous papers. Identifying the types of contributions an article makes can help readers quickly grasp its significance. The ACL Rolling Review (ARR) introduced a typology requiring authors to specify their contributions to improve review quality and fairness. However, the current typology lacks clear definitions and guidance, leading to inconsistent labeling and raising concerns about its reliability.Our re-annotation campaign reveals substantial disagreement between authors and domain experts. Moreover, the predictions of large language models (LLMs), when compared with expert annotations, tend to be close to those provided by the authors. These findings suggest a potential path toward better annotation reliability within the ARR process.
%U https://aclanthology.org/2026.findings-acl.178/
%P 3636-3653
Markdown (Informal)
[Towards Reliable Paper Contributions Annotation in the ACL Rolling Review](https://aclanthology.org/2026.findings-acl.178/) (Aubert-Béduchaud et al., Findings 2026)
ACL