LLM adaptive exploration via runtime code execution outperforms static query generation for information extraction from heterogeneous BIM models on the new ifc-bench v2 benchmark.
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IfcLLM combines relational and graph representations of IFC models with an LLM agent to achieve 93.3-100% first-attempt accuracy on natural language queries across three models and 30 scenarios.
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BIM Information Extraction Through LLM-based Adaptive Exploration
LLM adaptive exploration via runtime code execution outperforms static query generation for information extraction from heterogeneous BIM models on the new ifc-bench v2 benchmark.
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IfcLLM: Natural Language Querying of IFC Models through Complementary Relational and Graph Representations
IfcLLM combines relational and graph representations of IFC models with an LLM agent to achieve 93.3-100% first-attempt accuracy on natural language queries across three models and 30 scenarios.