Architext: Language-Driven Generative Architecture Design

• URL: http://arxiv.org/abs/2303.07519v3
• Date: Wed, 3 May 2023 09:29:05 GMT
• Title: Architext: Language-Driven Generative Architecture Design
• Authors: Theodoros Galanos, Antonios Liapis and Georgios N. Yannakakis
• Abstract summary: Architext enables design generation with only natural language prompts, given to large-scale Language Models, as input. We conduct a thorough quantitative evaluation of Architext's downstream task performance, focusing on semantic accuracy and diversity for a number of pre-trained language models. Architext models are able to learn the specific design task, generating valid residential layouts at a near 100% rate.
• Score: 1.393683063795544
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Architectural design is a highly complex practice that involves a wide diversity of disciplines, technologies, proprietary design software, expertise, and an almost infinite number of constraints, across a vast array of design tasks. Enabling intuitive, accessible, and scalable design processes is an important step towards performance-driven and sustainable design for all. To that end, we introduce Architext, a novel semantic generation assistive tool. Architext enables design generation with only natural language prompts, given to large-scale Language Models, as input. We conduct a thorough quantitative evaluation of Architext's downstream task performance, focusing on semantic accuracy and diversity for a number of pre-trained language models ranging from 120 million to 6 billion parameters. Architext models are able to learn the specific design task, generating valid residential layouts at a near 100% rate. Accuracy shows great improvement when scaling the models, with the largest model (GPT-J) yielding impressive accuracy ranging between 25% to over 80% for different prompt categories. We open source the finetuned Architext models and our synthetic dataset, hoping to inspire experimentation in this exciting area of design research.

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