{
  "id": 6490,
  "url": "https://arxiv.org/abs/2604.01020v1",
  "title": "OrgAgent: Organize Your Multi-Agent System like a Company",
  "summary": "While large language model-based multi-agent systems have shown strong potential for complex reasoning, how to effectively organize multiple agents remains an open question. In this paper, we introduce OrgAgent, a company-style hierarchical multi-agent framework that separates collaboration into governance, execution, and compliance layers. OrgAgent decomposes multi-agent reasoning into three layers: a governance layer for planning and resource allocation, an execution layer for task solving and",
  "authors": "Yiru Wang, Xinyue Shen, Yaohui Han, Michael Backes, Pin-Yu Chen, Tsung-Yi Ho",
  "category": "research",
  "topics": "regulation,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-01T15:21:14.000Z",
  "fetched_at": "2026-07-14T16:32:33.099Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6490",
  "original_url": "https://arxiv.org/abs/2604.01020v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}