9 papers
BIM Information Extraction Through LLM-based Adaptive Exploration
Sylvain Hellin, Suhyung Jang, Stefan Fuchs +2
BIM models provide structured representations of building geometry, semantics, and topology, yet extracting specific information from them remains remarkably difficult. Current app…
HodgeFormer: Transformers for Learnable Operators on Triangular Meshes through Data-Driven Hodge Matrices
Akis Nousias, Stavros Nousias
Currently, prominent Transformer architectures applied on graphs and meshes for shape analysis tasks employ traditional attention layers that heavily utilize spectral features requ…
Predictive Modeling: BIM Command Recommendation Based on Large-scale Usage Logs
Changyu Du, Zihan Deng, Stavros Nousias +1
The adoption of Building Information Modeling (BIM) and model-based design within the Architecture, Engineering, and Construction (AEC) industry has been hindered by the perception…
Text2BIM: Generating Building Models Using a Large Language Model-based Multi-Agent Framework
Changyu Du, Sebastian Esser, Stavros Nousias +1
The conventional BIM authoring process typically requires designers to master complex and tedious modeling commands in order to materialize their design intentions within BIM autho…
BIMgent: Towards Autonomous Building Modeling via Computer-use Agents
Zihan Deng, Changyu Du, Stavros Nousias +1
Existing computer-use agents primarily focus on general-purpose desktop automation tasks, with limited exploration of their application in highly specialized domains. In particular…
VectorGraphNET: Graph Attention Networks for Accurate Segmentation of Complex Technical Drawings
Andrea Carrara, Stavros Nousias, André Borrmann
This paper introduces a new approach to extract and analyze vector data from technical drawings in PDF format. Our method involves converting PDF files into SVG format and creating…