@inproceedings{zhao-etal-2026-rolearena,
title = "{R}ole{A}rena: Autonomous Plot Progression for Long-Horizon Multi-Agent Role-Playing",
author = "Zhao, Qi and
Li, Jian and
Jin, Yizhang and
Liu, Dongqi and
Ding, Hang and
Song, Qi and
Li, Xiang-Yang",
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.1160/",
pages = "24553--24576",
ISBN = "979-8-89176-462-0",
abstract = "Improving the plot progression ability of role-playing language agents (RPLAs) plays a critical role in enhancing user experience and dialogue immersion. However, research on plot progression in role-playing language agents is still limited. Existing datasets often contain too few dialogue turns and lack large-scale sentences with clear deterministic plot turns, which restricts further model development and evaluation. To bridge this gap, we propose RoleArena, an innovative multi-agent role-playing environment. By introducing a critic agent and combining discrete plot lines with environment-agent-based dynamic judgments, the system generates long multi-turn dialogues with key markers for plot progression. Based on RoleArena, we construct the PlotStream dataset, which contains 39.3k characters and 170k dialogues, with annotations for key plot progression sentences. In addition, based on PlotStream, we further develop PlotRole-7B and PlotRole-72B, RPLAs built upon the Qwen2.5 model and specialized in plot progression capabilities. Extensive experiments show that RoleArena and PlotRole improve dialogue generation with plot progression and strengthen the ability of plot progression."
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<abstract>Improving the plot progression ability of role-playing language agents (RPLAs) plays a critical role in enhancing user experience and dialogue immersion. However, research on plot progression in role-playing language agents is still limited. Existing datasets often contain too few dialogue turns and lack large-scale sentences with clear deterministic plot turns, which restricts further model development and evaluation. To bridge this gap, we propose RoleArena, an innovative multi-agent role-playing environment. By introducing a critic agent and combining discrete plot lines with environment-agent-based dynamic judgments, the system generates long multi-turn dialogues with key markers for plot progression. Based on RoleArena, we construct the PlotStream dataset, which contains 39.3k characters and 170k dialogues, with annotations for key plot progression sentences. In addition, based on PlotStream, we further develop PlotRole-7B and PlotRole-72B, RPLAs built upon the Qwen2.5 model and specialized in plot progression capabilities. Extensive experiments show that RoleArena and PlotRole improve dialogue generation with plot progression and strengthen the ability of plot progression.</abstract>
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%0 Conference Proceedings
%T RoleArena: Autonomous Plot Progression for Long-Horizon Multi-Agent Role-Playing
%A Zhao, Qi
%A Li, Jian
%A Jin, Yizhang
%A Liu, Dongqi
%A Ding, Hang
%A Song, Qi
%A Li, Xiang-Yang
%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 zhao-etal-2026-rolearena
%X Improving the plot progression ability of role-playing language agents (RPLAs) plays a critical role in enhancing user experience and dialogue immersion. However, research on plot progression in role-playing language agents is still limited. Existing datasets often contain too few dialogue turns and lack large-scale sentences with clear deterministic plot turns, which restricts further model development and evaluation. To bridge this gap, we propose RoleArena, an innovative multi-agent role-playing environment. By introducing a critic agent and combining discrete plot lines with environment-agent-based dynamic judgments, the system generates long multi-turn dialogues with key markers for plot progression. Based on RoleArena, we construct the PlotStream dataset, which contains 39.3k characters and 170k dialogues, with annotations for key plot progression sentences. In addition, based on PlotStream, we further develop PlotRole-7B and PlotRole-72B, RPLAs built upon the Qwen2.5 model and specialized in plot progression capabilities. Extensive experiments show that RoleArena and PlotRole improve dialogue generation with plot progression and strengthen the ability of plot progression.
%U https://aclanthology.org/2026.findings-emnlp.1160/
%P 24553-24576
Markdown (Informal)
[RoleArena: Autonomous Plot Progression for Long-Horizon Multi-Agent Role-Playing](https://aclanthology.org/2026.findings-emnlp.1160/) (Zhao et al., Findings 2026)
ACL