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ACL 2026longmain

Hetero-Designer: Automated Design of Multi-Agent Systems with Heterogeneous LLMs

Zhiheng Zhang, Yuanzhe Zhang, Bohan Yu, Daojian Zeng, Kang Liu, Jun Zhao

National Science Library, Chinese Academy of Sciences · Hunan Normal University · Institute of automation, Chinese academy of science, Chinese Academy of Sciences · Institute of automation, Chinese academy of science

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2026.acl-long.1272 ↗

摘要

LLM-based Multi-agent systems (MAS) have shown strong capabilities across a wide range of domains. Their success largely hinges on the collaboration topology design, which has emerged as a central research focus in the automated MAS design.However, existing approaches are fundamentally constrained by their reliance on homogeneous LLMs, which significantly limits overall system intelligence.In response to this limitation, we for the first time propose the concept of **Automated Design of Heterogeneous-LLMs-based MAS (ADHM)**.ADHM sheds light on a promising avenue for advancing collective intelligence, which focuses on the automated design of cost-effective MAS composed of diverse LLMsand roles to suit various queries.Toward this challenging goal, we propose **Hetero-Designer**, a novel pipeline that efficiently encodes intricate dependencies among queries, LLMs and roles through a novel Binary-Star Transformer and constructs Hetero-MAS in an autoregressive graph generation process. Extensive experiments demonstrate that **Hetero-Designer** is: (1) high-performing on various benchmarks, (2) economical in reducing overhead, (3) extensible to unseen LLMs and roles.