An LLM-Based Framework for Intent-Driven Network Topology Design
This work investigates the ability of Large Language Models to generate structurally valid and constraint-compliant network topologies through a constraint-driven pipeline combining hierarchical modeling and systematic validation, and provides a systematic benchmark for understanding how LLMs handle structural and resilience constraints in topology synthesis.