Explores design assistance using multimodal language models in collaborative design, suggesting enhanced idea detailing.
In this work, we propose a multimodal, language-model–based design assistance framework for the design ideation stage. The framework leverages large language models (LLMs) to interpret user intentions with mood boards, enrich initial ideas with essential contextual details, and produce structured instructions for visual language models (VLMs) to enhance the accuracy and consistency of visual feedback.
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Zhang et al. (2026) studied this question.
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