Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866915863890755584 |
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| author | Zhang, Xing Cui, Yanwei Wang, Guanghui Qiu, Wei Li, Ziyuan Han, Fangwei Huang, Yajing Qiu, Hengzhi Zhu, Bing He, Peiyang |
| author_facet | Zhang, Xing Cui, Yanwei Wang, Guanghui Qiu, Wei Li, Ziyuan Han, Fangwei Huang, Yajing Qiu, Hengzhi Zhu, Bing He, Peiyang |
| contents | We present Verified Multi-Agent Orchestration (VMAO), a framework that coordinates specialized LLM-based agents through a verification-driven iterative loop. Given a complex query, our system decomposes it into a directed acyclic graph (DAG) of sub-questions, executes them through domain-specific agents in parallel, verifies result completeness via LLM-based evaluation, and adaptively replans to address gaps. The key contributions are: (1) dependency-aware parallel execution over a DAG of sub-questions with automatic context propagation, (2) verification-driven adaptive replanning that uses an LLM-based verifier as an orchestration-level coordination signal, and (3) configurable stop conditions that balance answer quality against resource usage. On 25 expert-curated market research queries, VMAO improves answer completeness from 3.1 to 4.2 and source quality from 2.6 to 4.1 (1-5 scale) compared to a single-agent baseline, demonstrating that orchestration-level verification is an effective mechanism for multi-agent quality assurance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_11445 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution Zhang, Xing Cui, Yanwei Wang, Guanghui Qiu, Wei Li, Ziyuan Han, Fangwei Huang, Yajing Qiu, Hengzhi Zhu, Bing He, Peiyang Artificial Intelligence Multiagent Systems We present Verified Multi-Agent Orchestration (VMAO), a framework that coordinates specialized LLM-based agents through a verification-driven iterative loop. Given a complex query, our system decomposes it into a directed acyclic graph (DAG) of sub-questions, executes them through domain-specific agents in parallel, verifies result completeness via LLM-based evaluation, and adaptively replans to address gaps. The key contributions are: (1) dependency-aware parallel execution over a DAG of sub-questions with automatic context propagation, (2) verification-driven adaptive replanning that uses an LLM-based verifier as an orchestration-level coordination signal, and (3) configurable stop conditions that balance answer quality against resource usage. On 25 expert-curated market research queries, VMAO improves answer completeness from 3.1 to 4.2 and source quality from 2.6 to 4.1 (1-5 scale) compared to a single-agent baseline, demonstrating that orchestration-level verification is an effective mechanism for multi-agent quality assurance. |
| title | Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution |
| topic | Artificial Intelligence Multiagent Systems |
| url | https://arxiv.org/abs/2603.11445 |