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.
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.
arXiv:2607. 00015v1 Announce Type: cross Abstract: To improve residents' well-being in Australia's urban areas, governments have introduced policy reforms such as SEPP65, BADS, and SPP7.
arXiv:2606. 20146v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to computer-aided design (CAD) to generate design artifacts from textual instructions.
The paper introduces GLaMoR, a reasoning pipeline that converts OWL ontologies into graph-structured data and applies a Graph Language Model (GLM) for consistency checking. It addresses the challenge of verifying ontology consistency, especially for large ontologies where classical reasoners become computationally expensive. Experiments on NCBO BioPortal ontologies show that GLaMoR achieves 95% accuracy and is 20 times faster than traditional reasoners.
arXiv:2606. 17637v1 Announce Type: new Abstract: Building Management Systems (BMS) are essential for optimizing energy efficiency and operational performance in modern buildings.
arXiv:2605.14259v3 Announce Type: replace Abstract: Applying Large Language Models (LLMs) to heterogeneous enterprise systems is hindered by hallucinations and failures in multi-hop, n-ary reasoning....
arXiv:2602.11678v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual understanding, yet they suffer from a critical limitation: struct...
arXiv:2607. 22571v1 Announce Type: new Abstract: Knowledge Graph-based Retrieval-Augmented Generation (KG-RAG) enables natural language interaction with structured enterprise knowledge, yet existing agentic approaches that perform well on public benchmarks often fail to generalize to real-world enterprise Knowledge Graphs (KGs), which are dense, schema-driven, and operationally constrained.
arXiv:2510. 22204v3 Announce Type: replace-cross Abstract: Reliable assessment of safe landing sites in unstructured environments is essential for deploying Unmanned Aerial Vehicles (UAVs) in real-world applications such as delivery, inspection, and surveillance.
Code-as-Auditor is an LLM-based framework that transforms regulatory information into formal checklists and executable decision trees, encoding rules as interpretable code. During inference, the model expands each checklist item into factual and counterfactual questions, guiding reasoning over case-specific evidence and potential violations. This pipeline moves from evidence identification to rule application and final decision-making, with a self‑verification loop that enhances logical consistency and traceability, leading to more accurate and evidence‑backed compliance evaluations in privacy and data protection scenarios.
arXiv:2608.21418v1 Announce Type: new Abstract: Manufacturing knowledge graphs that integrate data from heterogeneous industrial systems face a trust deficit: consumers cannot determine whether queri...
arXiv:2607. 09578v1 Announce Type: new Abstract: Pre-demolition assessment, the regulated audit process at the heart of urban mining, is an information process in which AI support must serve qualified auditors who remain accountable for the decisions taken.