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contributor authorShea, Kristina
contributor authorStanković, Tino
contributor authorAgrawal, Akash
contributor authorCagan, Jonathan
contributor authorMcComb, Christopher
date accessioned2026-08-23T07:52:45Z
date available2026-08-23T07:52:45Z
date copyright2025/12/01
date issued2025
identifier issn1530-9827
identifier otherjcise-25-1260.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4315746
description abstractAbstract. Research in design grammars has been underway for over 50 years and has demonstrated great generative power for a wide range of design and engineering domains. A key limitation, though, is the lack of support for designers to develop and computationally implement formal design grammars. We explore the potential of large language models (LLMs) to act as a collaborative grammar development partner that works with human designers and provides guidance during grammar development, as well as serving as a grammar interpreter that converts natural language descriptions of design grammars into executable python code. Methods for both interpreting previously known design grammars as well as interactively and collaboratively developing a new design grammar that is not known a priori are proposed. Three case studies, namely a truss design grammar, a half-hexagon shape grammar, and a technical process grammar, are investigated, covering string, shape, and graph grammars to explore the advantages and limitations of combining design grammars and LLMs. Finally, we position formal design grammars to be a key element for the future to expand the generative power of LLMs and enable them to become more repeatable, precise, and explainable for generative design tasks.
publisherThe American Society of Mechanical Engineers (ASME)
titleExpanding the Generative Power of Large Language Models for Design Through Formal Design Grammars and Languages
typeJournal Paper
journal volume25
journal issue12
journal titleJournal of Computing and Information Science in Engineering
identifier doi10.1115/1.4070095
journal fristpage125
journal lastpage135
page11
treeJournal of Computing and Information Science in Engineering:;2025:;volume( 025 ):;issue:012
contenttypeFulltext


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