mlsanityData to 7 Oct 2026

Large Language Model-Driven Cross-Domain Orchestration Using Multi-Agent Workflow

arXiv 2410.10831 ↗First posted 28 Sep 2024cs.MAcited by 1

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

We showcase an application that leverages multiple agents, powered by large language models and integrated tools, to collaboratively solve complex network operation tasks across various domains. The tasks include real-time topology retrieval, network optimization using physical models, and fiber switching facilitated by a robotic arm.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 2 of its 6 references that are in the map. First posted on arXiv 28 Sep 2024.

Builds on

2 of 6 references.

References · 2

  1. 2023Large Language Models for Networking: Applications, Enabling Techniques, and Challengescited by 28
  2. 2023Digital Twin of a Network and Operating Environment Using Augmented Realitycited by 1

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Cited by year

Citing papers per year: 2025: 1.

1 paper.

  1. 2025Reflection-Driven Self-Optimization 6G Agentic AI RAN via Simulation-in-the-Loop Workflowscited by 2

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  6. 2026SwarmBench: Can Large Language Models Act as Agent Swarm Orchestrators?
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