# Text-to-Layout: A Generative Workflow for Drafting Architectural Floor Plans Using LLMs

arXiv: https://arxiv.org/abs/2509.00543 · HTML: https://mlsanity.com/paper/2509.00543/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 35 references that are in the map.
- First posted on arXiv 30 Aug 2025.

## Builds on (most cited first, 6 of 6)

- [GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models](https://mlsanity.com/paper/2112.10741/) (2021)
- [Generative AI Models for Different Steps in Architectural Design: A Literature Review](https://mlsanity.com/paper/2404.01335/) (2024)
- [Large Language Model-Driven Code Compliance Checking in Building Information Modeling](https://mlsanity.com/paper/2506.20551/) (2025)
- [Automating Computational Design with Generative AI](https://mlsanity.com/paper/2307.02511/) (2023)
- [Integrating Generative AI in BIM Education: Insights from Classroom Implementation](https://mlsanity.com/paper/2507.05296/) (2025)
- [LLM4DESIGN: An Automated Multi-Modal System for Architectural and Environmental Design](https://mlsanity.com/paper/2407.12025/) (2024)

## Built on by (most cited first, 2 of 2)

- [MCP4IFC: IFC-Based Building Design Using Large Language Models](https://mlsanity.com/paper/2511.05533/) (2025)
- [A Modular Reference Architecture for MCP-Servers Enabling Agentic BIM Interaction](https://mlsanity.com/paper/2601.00809/) (2025)

## Abstract (arXiv)

This paper presents the development of an AI-powered workflow that uses Large Language Models (LLMs) to assist in drafting schematic architectural floor plans from natural language prompts. The proposed system interprets textual input to automatically generate layout options including walls, doors, windows, and furniture arrangements. It combines prompt engineering, a furniture placement refinement algorithm, and Python scripting to produce spatially coherent draft plans compatible with design tools such as Autodesk Revit. A case study of a mid-sized residential layout demonstrates the approach's ability to generate functional and structured outputs with minimal manual effort. The workflow is designed for transparent replication, with all key prompt specifications documented to enable independent implementation by other researchers. In addition, the generated models preserve the full range of Revit-native parametric attributes required for direct integration into professional BIM processes.