mlsanityData to 7 Oct 2026

TopoEdge: Topology-Grounded Agentic Framework for Edge Networking Code Generation and Repair

arXiv 2603.00569 ↗First posted 28 Feb 2026cs.SE cs.LG cs.NIcited by 0

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Abstract (arXiv)

TopoEdge is a topology-grounded, edge-deployable framework for end-to-end software-defined networking (SDN) configuration generation and repair, motivated by the brittleness of configuration artefacts under topology variation and by strict operational constraints on latency, privacy, and on-site execution. TopoEdge represents each target topology as a router-level graph and embeds it using a contrastively trained graph neural network (GNN), enabling nearest-neighbour retrieval of a verified reference configuration paired with an executable Python driver (a Topotest/pytest test script that orchestrates the emulated network and checks protocol assertions). The target topology, retrieved reference topology, and reference driver are assembled into a topology-grounded retrieval-augmented generation context (TopoRAG), which grounds a distributed, execution-centric generate--verify--repair loop coordinated by a central controller and realised by three role-specialised agents: (i) a Planning agent that produces a topology-consistent configuration plan and a per-device skeleton; (ii) a Generation agent that materialises executable configuration artefacts, including device configurations and the driver; and (iii) a Verification agent that runs the FRRouting Topotest/pytest harness, compresses failures into a compact trace, and emits localised patch directives for iterative repair.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 13 references that are in the map. First posted on arXiv 28 Feb 2026.

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7 of 13 references.

References · 7

  1. 2018Representation Learning with Contrastive Predictive Codingcited by 7,662
  2. 2022Fast Inference from Transformers via Speculative Decodingcited by 1,615
  3. 2023Efficient Large Language Models: A Surveycited by 183
  4. 2023Architectures of Topological Deep Learning: A Survey of Message-Passing Topological Neural Networkscited by 43
  5. 2024TopoBench: A Framework for Benchmarking Topological Deep Learningcited by 24
  6. 2024Large Language Models for Zero Touch Network Configuration Managementcited by 9
  7. 2025GraphCue for SDN Configuration Code Synthesiscited by 1

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  2. 2026Evaluating Agentic Configuration Repair for Computer Networks
  3. 2026TopoBench: Benchmarking LLMs on Hard Topological Reasoning
  4. 2026Topology-Consistent Task Planning over Cellular Workflow Complexes for LLM-based Agents
  5. 2025Agint: Agentic Graph Compilation for Software Engineering Agents
  6. 2024GeNet: A Multimodal LLM-Based Co-Pilot for Network Topology and Configuration
  7. 2026TopoEvo: A Topology-Aware Self-Evolving Multi-Agent Framework for Root Cause Analysis in Microservices
  8. 2026GraphBit: A Graph-based Agentic Framework for Non-Linear Agent Orchestration