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Automating Geometry-Intensive Compliance Checking in BIM: Graph-Based Semantic Reasoning Framework

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arXiv:2606. 12065v1 Announce Type: new Abstract: 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.

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Authors: Zixuan Xiao, Pei Troh Koh, Jun Ma, Jack C. P. Cheng
Released: 2026-06-11 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Automating Geometry-Intensive Compliance Checking in BIM: Graph-Based Semantic Reasoning Framework overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: code, line, without, chain, model. Source: arxiv cs.AI (Artificial Intelligence).
arXiv: 2606.12065

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