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English(EN) A Hybrid Framework for Natural Language Querying of IFC Models with Relational and Graph Representations

新框架支持对复杂BIM数据进行自然语言查询

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了IfcLLM，一个旨在通过自然语言查询使Industry Foundation Classes (IFC) 数据更易于访问的新型框架。该系统将IFC模型转换为关系和图表示，然后由具有迭代推理能力的LLM进行处理以理解用户请求。该框架使用开源GPT OSS 120B模型实现，在测试中表现出高准确性，为更直观地与复杂BIM数据交互指明了方向。 AI

影响 通过支持与复杂BIM数据的自然语言交互，该框架可以显著提高AEC行业非专业用户的可访问性。

排序理由 该集群描述了一篇介绍新框架及其评估的研究论文。

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新框架支持对复杂BIM数据进行自然语言查询

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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Johnson Xuesong Shen ·

    用于IFC模型自然语言查询的混合框架，结合关系型和图表示

    Building Information Modeling (BIM) is widely used in the Architecture, Engineering, and Construction (AEC) industry, but the complexity of Industry Foundation Classes (IFC) limits accessibility for non-expert users. To address this, we introduce IfcLLM, a hybrid framework for na…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    用于IFC模型自然语言查询的混合框架，包含关系型和图表示

    Building Information Modeling (BIM) is widely used in the Architecture, Engineering, and Construction (AEC) industry, but the complexity of Industry Foundation Classes (IFC) limits accessibility for non-expert users. To address this, we introduce IfcLLM, a hybrid framework for na…

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