@Article{	  eInformatica2026Art09,
  author	= {Hartwig Grabowski},
  title		= {A Modular Multi-Agent {LLM} Architecture for Text-to-Diagram Generation and User-Guided Refinement},
  doi		= {10.37190/e-Inf260109},
  year		= {2026},
  volume	= {20},
  number	= {1},
  keywords	= {diagram generation, multi-agent LLM pipeline, engineering informatics, automated modeling, computational design},
  journal	= {e-Informatica Software Engineering Journal},
  url		= {https://www.e-informatyka.pl/EISEJ/papers/2026/1/9/},
  abstract	= { Context: Recent advances in LLM-based diagram generation increasingly rely on coordinated agent systems rather than single-model prompts. Objective: This work highlights how modular multi-agent architectures improve reliability, semantic grounding, and iterative refinement in text-to-diagram workflows. Method: We analyze a pipeline composed of specialized agents for interpretation, synthesis, validation, and correction, each contributing a bounded and inspectable transformation. Results: The agent system provides deterministic validation, structured reasoning, and controlled refinement loops that outperform monolithic LLM generation. Conclusions: Multi-agent LLM pipelines represent a robust foundation for precise, verifiable diagram generation and serve as a reproducible alternative to single-pass text-to-diagram models. },
  note		= {Available online: 13 May 2026},
  month		= may,
  pages		= {260109}
}