Automating Geometry-Intensive Compliance Checking in BIM: Graph-Based Semantic Reasoning Framework
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Abstract (arXiv)
Automating compliance check for geometry-intensive regulations remains a significant technical bottleneck in Building Information Modeling (BIM), primarily due to the semantic disparity between high-level regulatory logic and structured IFC data. Existing methods, often reliant on static rule templates, struggle to traverse multi-hop reasoning chains or resolve latent spatial dependencies across multiple building entities. To address these challenges, a Spatial-Geometric Reasoning System for Building Information Modeling (SGR-BIM) is proposed as an integrative graph-driven reasoning framework. SGR-BIM dynamically constructs a cross-modal knowledge graph that aligns user intent, regulatory semantics, and BIM geometry, enabling interpretable reasoning without rigid hard-coding. Validated on 679 expert-verified queries from fire safety codes, the framework achieves 84.3% accuracy, representing an 8.6% improvement over enhanced-tool single-agent baselines. This research provides a graph-based semantic reasoning paradigm, enhancing the transparency and flexibility of automated geometric compliance check workflows in the Architecture, Engineering, and Construction (AEC) industry.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 7 of its 36 references that are in the map. First posted on arXiv 10 Jun 2026.
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7 of 36 references.
References · 7
- 2021VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioningcited by 191
- 2022NLP-based Automated Compliance Checking of Data Processing Agreements against GDPRcited by 18
- 2020Few-shot Object Detection with Self-adaptive Attention Network for Remote Sensing Imagescited by 14
- 2024Cypher4BIM: Releasing the Power of Graph for Building Knowledge Discoverycited by 2
- 2026LLM Agent Framework for Intelligent Change Analysis in Urban Environment using Remote Sensing Imagerycited by 2
- 2025Predictive Modeling: BIM Command Recommendation Based on Large-scale Usage Logscited by 1
- 2026MMUEChange: A Generalized LLM Agent Framework for Intelligent Multi-Modal Urban Environment Change Analysiscited by 1
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Citing papers per year: 2026: 1.
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- 2024Using Large Language Models for the Interpretation of Building Regulations
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- 2025Bridging Dual Knowledge Graphs for Multi-Hop Question Answering in Construction Safety
- 2026Ishigaki-IDS: An Open-Weight Verifier-Aware Model for Information Delivery Specification Drafting in Building Information Modeling