AI Navigate

Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution

arXiv cs.AI / 3/13/2026

📰 NewsDeveloper Stack & InfrastructureModels & Research

Key Points

  • VMAO is a verification-driven multi-agent orchestration framework that coordinates specialized LLM-based agents through a plan-execute-verify-replan loop on a directed acyclic graph of sub-questions.
  • It decomposes complex queries into a DAG and executes sub-questions in parallel with dependency-aware context propagation to improve efficiency.
  • It employs an LLM-based verifier at the orchestration level to evaluate result completeness and drive adaptive replanning to address gaps.
  • It offers configurable stop conditions to balance answer quality against resource usage and shows improved performance on 25 expert-curated market research queries (completeness 3.1→4.2; source quality 2.6→4.1 on a 1–5 scale) versus a single-agent baseline.

Abstract

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.