Intelligent Co-Design: An Interactive LLM Framework for Interior Spatial Design via Multi-Modal Agents

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• The LLM-based, multimodal, multi-agent framework dynamically converts natural language descriptions and imagery into 3D interior designs.method 95%
• The framework's specialized agent system enables real-time user interaction for iterative spatial refinement.technical 90%
• The framework's use of Retrieval-Augmented Generation (RAG) reduces data dependency without requiring task-specific model training.technical 90%
• An independent LLM evaluator consistently rated participatory layouts generated by the framework higher in user intent alignment, aesthetic coherence, functionality, and circulation.result 85%
• User questionnaire results indicated 77% satisfaction and a clear preference for the framework over traditional design software.result 85%
• The framework improves productivity and encourages non-designer participation in interior spatial design.result 80%
• Prevailing rule-based design systems implement hard-coded spatial constraints that restrict participatory engagement.limitation 90%
• Prevailing data-driven design models rely on extensive training datasets.limitation 90%

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