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GeNet: A Multimodal LLM-Based Co-Pilot for Network Topology and Configuration

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arxiv 2407.08249 v2 pith:GEO7DEKY submitted 2024-07-11 cs.NI cs.AI

classification cs.NIcs.AI
keywords networkgenettopologyenterpriseco-pilotconfigurationdesignengineering
verification ladder T0 review T1 audit T2 compute T3 formal
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Communication network engineering in enterprise environments is traditionally a complex, time-consuming, and error-prone manual process. Most research on network engineering automation has concentrated on configuration synthesis, often overlooking changes in the physical network topology. This paper introduces GeNet, a multimodal co-pilot for enterprise network engineers. GeNet is a novel framework that leverages a large language model (LLM) to streamline network design workflows. It uses visual and textual modalities to interpret and update network topologies and device configurations based on user intents. GeNet was evaluated on enterprise network scenarios adapted from Cisco certification exercises. Our results demonstrate GeNet's ability to interpret network topology images accurately, potentially reducing network engineers' efforts and accelerating network design processes in enterprise environments. Furthermore, we show the importance of precise topology understanding when handling intents that require modifications to the network's topology.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. LLM-Based Config Synthesis requires Disambiguation

    cs.NI 2025-07 conditional novelty 6.0 of 10

    LLM-based incremental config synthesis needs user disambiguation of insertion placement; Clarify uses differential questions and binary search to resolve it.

  2. AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives

    cs.NI 2025-09 conditional novelty 4.0 of 10

    A survey that organizes LLM and AI reasoning methods into a taxonomy and maps them onto the physical, link, network, transport, and application layers of wireless networks.

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