mlsanityData to 14 Oct 2026

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

arXiv 2603.11445 ↗First posted 12 Mar 2026cs.AI cs.MAcited by 10

On the map: LLM agents and tool use → Web, search, and research agents

Abstract (arXiv)

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.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 15 of its 17 references that are in the map. First posted on arXiv 12 Mar 2026.

Builds on

15 of 17 references.

References · 15

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
  4. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,276
  5. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  6. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  7. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,211
  8. 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
  9. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  10. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,947
  11. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,808
  12. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,784
3 more
  1. 2023The Rise and Potential of Large Language Model Based Agents: A Surveycited by 1,439
  2. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,395
  3. 2023HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Facecited by 1,190

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 10.

10 papers.

  1. 2026AutoPyVerifier: Learning Compact Executable Verifiers for Large Language Model Outputscited by 7
  2. 2026Self-Evolving Agents as Dynamic Graph Transformation: A Survey and New Perspectivecited by 4
  3. 2026Experience as a Compass: Multi-agent RAG with Evolving Orchestration and Agent Promptscited by 3
  4. 2026Prompt Optimization Is a Coin Flip: Diagnosing When It Helps in Compound AI Systemscited by 3
  5. 2026Clarus: Coordinating Autonomous Research Agents toward Web-Scale Scientific Collaborationcited by 0
  6. 2026EASy: Towards Efficient LLM-Based Agentic Systemcited by 0
  7. 2026SBCO: Self-Supervised, Verifier-Grounded Harness Optimization For Planning Agentscited by 0
  8. 2026Reconcile Once, Write Anytime: A Trust-Tiered Librarian and a Multi-Agent Writer for Drift-Free, Point-in-Time Researchcited by 0
  9. 2026UnitBoost: Managing Compound LLM Systems with a Merge Operator, Not a Modelcited by 0
  10. 2026A Hybrid Dependency-Aware Framework for Task Decomposition and Dynamic Agent Generation in Oracle-to-PostgreSQL Migrationcited by 0

Similar, not cited

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  3. 2026FineVerify: Scaling Test-Time Compute with Fine-Grained Self-Verification for Agentic Search
  4. 2026Competence-Aware Orchestration for LLM-Based Multi-Agent Systems
  5. 2026Decentralized Multi-Agent Systems with Shared Context
  6. 2026Utility-Guided Agent Orchestration for Efficient LLM Tool Use
  7. 2026Coordination as an Architectural Layer for LLM-Based Multi-Agent Systems
  8. 2025Beyond the Strongest LLM: Multi-Turn Multi-Agent Orchestration vs. Single LLMs on Benchmarks