@inproceedings{faulkner-etal-2026-simulating,
title = "Simulating Democratic Deliberation: Representing Pluralistic Preferences through Electoral Systems in Multi-Agent {LLM}s",
author = "Faulkner, Ryan and
Szufa, Stanis{\l}aw and
Hoyer, Daniel and
Zhang, Terry Jingchen and
Bouffanais, Roland and
Leibo, Joel Z and
Jin, Zhijing",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2026",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.findings-emnlp.554/",
pages = "11673--11705",
ISBN = "979-8-89176-462-0",
abstract = "Voting steers representation in democratic bodies and functions as the primary mechanism for imposing the social will of the electorate upon the decision making machinery of regional government. Citizens will often have diverse, and conflicting, viewpoints which makes faithful representation of their plural interests a serious challenge in multi-party democracies. In the context of multi-agent LLMs, pluralistic preference alignment addresses this problem and, often through deliberative and voting methodologies, aims to draw groups toward a common policy that consistently bridges together a range of individual preferences. However, in multi-agent settings where the goal is to craft policy satisfying very diverse preferences, such as in social or political scenarios, there is little understanding of how to structure general process mechanisms that lead to the best outcome. To address this we present VoteSim, a framework to simulate a wide range of electoral systems across sociopolitical topics and a diverse set of personalized voter LLM agents. We draw on a rich persona modeling dataset, a range of relevant sociopolitical topics, and prevalent legislative procedure to generate social policy through deliberation. Voting agents then rank their preferred policy to determine how electoral systems can satisfy group preference. Detailed empirical analysis reveals that pluralistic alignment in multi-agent LLMs on important sociopolitical issues is best achieved through proportional electoral representation, reflecting outcomes among multi-party systems in human society."
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<abstract>Voting steers representation in democratic bodies and functions as the primary mechanism for imposing the social will of the electorate upon the decision making machinery of regional government. Citizens will often have diverse, and conflicting, viewpoints which makes faithful representation of their plural interests a serious challenge in multi-party democracies. In the context of multi-agent LLMs, pluralistic preference alignment addresses this problem and, often through deliberative and voting methodologies, aims to draw groups toward a common policy that consistently bridges together a range of individual preferences. However, in multi-agent settings where the goal is to craft policy satisfying very diverse preferences, such as in social or political scenarios, there is little understanding of how to structure general process mechanisms that lead to the best outcome. To address this we present VoteSim, a framework to simulate a wide range of electoral systems across sociopolitical topics and a diverse set of personalized voter LLM agents. We draw on a rich persona modeling dataset, a range of relevant sociopolitical topics, and prevalent legislative procedure to generate social policy through deliberation. Voting agents then rank their preferred policy to determine how electoral systems can satisfy group preference. Detailed empirical analysis reveals that pluralistic alignment in multi-agent LLMs on important sociopolitical issues is best achieved through proportional electoral representation, reflecting outcomes among multi-party systems in human society.</abstract>
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%0 Conference Proceedings
%T Simulating Democratic Deliberation: Representing Pluralistic Preferences through Electoral Systems in Multi-Agent LLMs
%A Faulkner, Ryan
%A Szufa, Stanisław
%A Hoyer, Daniel
%A Zhang, Terry Jingchen
%A Bouffanais, Roland
%A Leibo, Joel Z.
%A Jin, Zhijing
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Findings of the Association for Computational Linguistics: EMNLP 2026
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-462-0
%F faulkner-etal-2026-simulating
%X Voting steers representation in democratic bodies and functions as the primary mechanism for imposing the social will of the electorate upon the decision making machinery of regional government. Citizens will often have diverse, and conflicting, viewpoints which makes faithful representation of their plural interests a serious challenge in multi-party democracies. In the context of multi-agent LLMs, pluralistic preference alignment addresses this problem and, often through deliberative and voting methodologies, aims to draw groups toward a common policy that consistently bridges together a range of individual preferences. However, in multi-agent settings where the goal is to craft policy satisfying very diverse preferences, such as in social or political scenarios, there is little understanding of how to structure general process mechanisms that lead to the best outcome. To address this we present VoteSim, a framework to simulate a wide range of electoral systems across sociopolitical topics and a diverse set of personalized voter LLM agents. We draw on a rich persona modeling dataset, a range of relevant sociopolitical topics, and prevalent legislative procedure to generate social policy through deliberation. Voting agents then rank their preferred policy to determine how electoral systems can satisfy group preference. Detailed empirical analysis reveals that pluralistic alignment in multi-agent LLMs on important sociopolitical issues is best achieved through proportional electoral representation, reflecting outcomes among multi-party systems in human society.
%U https://aclanthology.org/2026.findings-emnlp.554/
%P 11673-11705
Markdown (Informal)
[Simulating Democratic Deliberation: Representing Pluralistic Preferences through Electoral Systems in Multi-Agent LLMs](https://aclanthology.org/2026.findings-emnlp.554/) (Faulkner et al., Findings 2026)
ACL