@inproceedings{jia-etal-2025-agentstore,
title = "{A}gent{S}tore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant",
author = "Jia, Chengyou and
Luo, Minnan and
Dang, Zhuohang and
Sun, Qiushi and
Xu, Fangzhi and
Hu, Junlin and
Xie, Tianbao and
Wu, Zhiyong",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-acl.466/",
doi = "10.18653/v1/2025.findings-acl.466",
pages = "8908--8934",
ISBN = "979-8-89176-256-5",
abstract = "Digital agents capable of automating complex computer tasks have attracted considerable attention. However, existing agent methods exhibit deficiencies in their generalization and specialization capabilities, especially in handling open-ended computer tasks in real-world environments. Inspired by the rich functionality of the App store, we present AgentStore, a scalable platform designed to dynamically integrate heterogeneous agents for automating computer tasks. AgentStore allows the system to continuously enrich its capabilities and adapt to rapidly evolving operating systems. Additionally, we propose a novel core MetaAgent with the AgentToken strategy to efficiently manage diverse agents and utilize their specialized and generalist abilities for both domain-specific and system-wide tasks. Extensive experiments on three interactive real-world benchmarks demonstrate that AgentStore significantly expands the capability boundaries of agent systems in both generalization and specialization, underscoring its potential for developing the specialized generalist computer assistant."
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<abstract>Digital agents capable of automating complex computer tasks have attracted considerable attention. However, existing agent methods exhibit deficiencies in their generalization and specialization capabilities, especially in handling open-ended computer tasks in real-world environments. Inspired by the rich functionality of the App store, we present AgentStore, a scalable platform designed to dynamically integrate heterogeneous agents for automating computer tasks. AgentStore allows the system to continuously enrich its capabilities and adapt to rapidly evolving operating systems. Additionally, we propose a novel core MetaAgent with the AgentToken strategy to efficiently manage diverse agents and utilize their specialized and generalist abilities for both domain-specific and system-wide tasks. Extensive experiments on three interactive real-world benchmarks demonstrate that AgentStore significantly expands the capability boundaries of agent systems in both generalization and specialization, underscoring its potential for developing the specialized generalist computer assistant.</abstract>
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%0 Conference Proceedings
%T AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant
%A Jia, Chengyou
%A Luo, Minnan
%A Dang, Zhuohang
%A Sun, Qiushi
%A Xu, Fangzhi
%A Hu, Junlin
%A Xie, Tianbao
%A Wu, Zhiyong
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Findings of the Association for Computational Linguistics: ACL 2025
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-256-5
%F jia-etal-2025-agentstore
%X Digital agents capable of automating complex computer tasks have attracted considerable attention. However, existing agent methods exhibit deficiencies in their generalization and specialization capabilities, especially in handling open-ended computer tasks in real-world environments. Inspired by the rich functionality of the App store, we present AgentStore, a scalable platform designed to dynamically integrate heterogeneous agents for automating computer tasks. AgentStore allows the system to continuously enrich its capabilities and adapt to rapidly evolving operating systems. Additionally, we propose a novel core MetaAgent with the AgentToken strategy to efficiently manage diverse agents and utilize their specialized and generalist abilities for both domain-specific and system-wide tasks. Extensive experiments on three interactive real-world benchmarks demonstrate that AgentStore significantly expands the capability boundaries of agent systems in both generalization and specialization, underscoring its potential for developing the specialized generalist computer assistant.
%R 10.18653/v1/2025.findings-acl.466
%U https://aclanthology.org/2025.findings-acl.466/
%U https://doi.org/10.18653/v1/2025.findings-acl.466
%P 8908-8934
Markdown (Informal)
[AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant](https://aclanthology.org/2025.findings-acl.466/) (Jia et al., Findings 2025)
ACL
- Chengyou Jia, Minnan Luo, Zhuohang Dang, Qiushi Sun, Fangzhi Xu, Junlin Hu, Tianbao Xie, and Zhiyong Wu. 2025. AgentStore: Scalable Integration of Heterogeneous Agents As Specialized Generalist Computer Assistant. In Findings of the Association for Computational Linguistics: ACL 2025, pages 8908–8934, Vienna, Austria. Association for Computational Linguistics.