@inproceedings{shi-cocarascu-2026-argument,
title = "Argument Summarization: A Unified Task Definition, Taxonomy, and Survey",
author = "Shi, Zhiqiang and
Cocarascu, Oana",
editor = "Zhang, Yue and
Xu, Ruifeng and
Purwarianti, Ayu and
Rong, Tong and
Suzuki, Jun",
booktitle = "Proceedings of the 15th International Joint Conference on Natural Language Processing and the 5th Conference of the {A}sia-Pacific Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = nov,
year = "2026",
address = "Hengqin, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.aacl-long.15/",
pages = "307--319",
ISBN = "979-8-89176-439-2",
abstract = "Argument summarization seeks to generate concise representations of argumentative content while preserving argumentative meaning, yet the field remains conceptually fragmented. In this survey, we provide a unified task definition of argument summarization that encompasses both argumentative text summarization and key point analysis, and introduce a taxonomy along input structure, output representation, and the role of argumentative structure. Using this framework, we analyze the evolution of the field and systematically review existing datasets, methods, and evaluation practices, revealing misalignment that hinders comparability and progress. We further situate argument summarization within the broader context of generic text summarization, identifying practical limitations and intrinsic challenges. Finally, we outline promising future research directions."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="shi-cocarascu-2026-argument">
<titleInfo>
<title>Argument Summarization: A Unified Task Definition, Taxonomy, and Survey</title>
</titleInfo>
<name type="personal">
<namePart type="given">Zhiqiang</namePart>
<namePart type="family">Shi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Oana</namePart>
<namePart type="family">Cocarascu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2026-11</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 15th International Joint Conference on Natural Language Processing and the 5th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Yue</namePart>
<namePart type="family">Zhang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ruifeng</namePart>
<namePart type="family">Xu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ayu</namePart>
<namePart type="family">Purwarianti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tong</namePart>
<namePart type="family">Rong</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jun</namePart>
<namePart type="family">Suzuki</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Hengqin, China</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-439-2</identifier>
</relatedItem>
<abstract>Argument summarization seeks to generate concise representations of argumentative content while preserving argumentative meaning, yet the field remains conceptually fragmented. In this survey, we provide a unified task definition of argument summarization that encompasses both argumentative text summarization and key point analysis, and introduce a taxonomy along input structure, output representation, and the role of argumentative structure. Using this framework, we analyze the evolution of the field and systematically review existing datasets, methods, and evaluation practices, revealing misalignment that hinders comparability and progress. We further situate argument summarization within the broader context of generic text summarization, identifying practical limitations and intrinsic challenges. Finally, we outline promising future research directions.</abstract>
<identifier type="citekey">shi-cocarascu-2026-argument</identifier>
<location>
<url>https://aclanthology.org/2026.aacl-long.15/</url>
</location>
<part>
<date>2026-11</date>
<extent unit="page">
<start>307</start>
<end>319</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Argument Summarization: A Unified Task Definition, Taxonomy, and Survey
%A Shi, Zhiqiang
%A Cocarascu, Oana
%Y Zhang, Yue
%Y Xu, Ruifeng
%Y Purwarianti, Ayu
%Y Rong, Tong
%Y Suzuki, Jun
%S Proceedings of the 15th International Joint Conference on Natural Language Processing and the 5th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 November
%I Association for Computational Linguistics
%C Hengqin, China
%@ 979-8-89176-439-2
%F shi-cocarascu-2026-argument
%X Argument summarization seeks to generate concise representations of argumentative content while preserving argumentative meaning, yet the field remains conceptually fragmented. In this survey, we provide a unified task definition of argument summarization that encompasses both argumentative text summarization and key point analysis, and introduce a taxonomy along input structure, output representation, and the role of argumentative structure. Using this framework, we analyze the evolution of the field and systematically review existing datasets, methods, and evaluation practices, revealing misalignment that hinders comparability and progress. We further situate argument summarization within the broader context of generic text summarization, identifying practical limitations and intrinsic challenges. Finally, we outline promising future research directions.
%U https://aclanthology.org/2026.aacl-long.15/
%P 307-319
Markdown (Informal)
[Argument Summarization: A Unified Task Definition, Taxonomy, and Survey](https://aclanthology.org/2026.aacl-long.15/) (Shi & Cocarascu, AACL-IJCNLP 2026)
ACL
- Zhiqiang Shi and Oana Cocarascu. 2026. Argument Summarization: A Unified Task Definition, Taxonomy, and Survey. In Proceedings of the 15th International Joint Conference on Natural Language Processing and the 5th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 307–319, Hengqin, China. Association for Computational Linguistics.