mlsanityData to 14 Oct 2026

Interactive Design by Integrating a Large Pre-Trained Language Model and Building Information Modeling

arXiv 2306.14165 ↗First posted 25 Jun 2023cs.AI cs.HCcited by 5

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Abstract (arXiv)

This study explores the potential of generative artificial intelligence (AI) models, specifically OpenAI's generative pre-trained transformer (GPT) series, when integrated with building information modeling (BIM) tools as an interactive design assistant for architectural design. The research involves the development and implementation of three key components: 1) BIM2XML, a component that translates BIM data into extensible markup language (XML) format; 2) Generative AI-enabled Interactive Architectural design (GAIA), a component that refines the input design in XML by identifying designer intent, relevant objects, and their attributes, using pre-trained language models; and 3) XML2BIM, a component that converts AI-generated XML data back into a BIM tool. This study validated the proposed approach through a case study involving design detailing, using the GPT series and Revit. Our findings demonstrate the effectiveness of state-of-the-art language models in facilitating dynamic collaboration between architects and AI systems, highlighting the potential for further advancements.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 3 of its 13 references that are in the map. First posted on arXiv 25 Jun 2023.

Builds on

3 of 13 references.

References · 3

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2023GPT-4 Technical Reportcited by 18,396
  3. 2021An adaptive artificial neural network-based generative design method for layout designscited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 2; 2026: 1.

5 papers.