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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.12025 |
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| _version_ | 1866913434211188736 |
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| author | Chen, Ran Yao, Xueqi Jiang, Xuhui |
| author_facet | Chen, Ran Yao, Xueqi Jiang, Xuhui |
| contents | This study introduces LLM4DESIGN, a highly automated system for generating architectural and environmental design proposals. LLM4DESIGN, relying solely on site conditions and design requirements, employs Multi-Agent systems to foster creativity, Retrieval Augmented Generation (RAG) to ground designs in realism, and Visual Language Models (VLM) to synchronize all information. This system resulting in coherent, multi-illustrated, and multi-textual design schemes. The system meets the dual needs of narrative storytelling and objective drawing presentation in generating architectural and environmental design proposals. Extensive comparative and ablation experiments confirm the innovativeness of LLM4DESIGN's narrative and the grounded applicability of its plans, demonstrating its superior performance in the field of urban renewal design. Lastly, we have created the first cross-modal design scheme dataset covering architecture, landscape, interior, and urban design, providing rich resources for future research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_12025 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | LLM4DESIGN: An Automated Multi-Modal System for Architectural and Environmental Design Chen, Ran Yao, Xueqi Jiang, Xuhui Human-Computer Interaction Artificial Intelligence This study introduces LLM4DESIGN, a highly automated system for generating architectural and environmental design proposals. LLM4DESIGN, relying solely on site conditions and design requirements, employs Multi-Agent systems to foster creativity, Retrieval Augmented Generation (RAG) to ground designs in realism, and Visual Language Models (VLM) to synchronize all information. This system resulting in coherent, multi-illustrated, and multi-textual design schemes. The system meets the dual needs of narrative storytelling and objective drawing presentation in generating architectural and environmental design proposals. Extensive comparative and ablation experiments confirm the innovativeness of LLM4DESIGN's narrative and the grounded applicability of its plans, demonstrating its superior performance in the field of urban renewal design. Lastly, we have created the first cross-modal design scheme dataset covering architecture, landscape, interior, and urban design, providing rich resources for future research. |
| title | LLM4DESIGN: An Automated Multi-Modal System for Architectural and Environmental Design |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2407.12025 |