Intelligent Identification and Repair of Design Defects in BIM via Domain-Specific Large Language Models
Existing methods lack a generalized approach to efficiently identify and resolve the diversity of design defects in BIM. Therefore, this study proposes an integrated framework to identify and repair various defects in BIM via domain-specific LLMs. Firstly, a BIM-to-Text method with component-balanced chunking is introduced to bridge BIM data with LLMs. Then, prompt learning with rule injection, few-shot prompting and RAG is proposed to identify defects and generate repair suggestions. Meanwhile, a hallucination control strategy combining key identifier validation and token-length thresholds is introduced to ensure reliability. Experiments show capability expansion yields 85% identificatio...
| Authors | Jia-Rui Lin, Yun-Hong Cai, Xiang-Rui Ni et al. |
|---|---|
| Primary category | cs.CL |
| Published | 2 August 2026 |
| Last updated at source | 2 August 2026 |
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