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arXiv — cs.AI

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GEMS-RAG: Graph-grounded Engineering Multimodal Standards Retrieval-Augmented Generation

arXiv:2610.33277v1 Announce Type: new Abstract: Engineering standards are challenging knowledge sources for large language models (LLMs) because they are hierarchical, multimodal, and densely connected through figures, tables, cross-references, and normative rules. Existing…

arXiv — cs.AIBy: Abdul Hannan Azad, Irvin Wang, Jiwan Jiang, Chenchen Kuai, Bofeng Cao, Keshu Wu, Yuzhou Wang, Xiaopeng Li, Yang ZhouOctober 27, 2026 (yesterday)
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  • arXiv:2610.33277v1 Announce Type: new Abstract: Engineering standards are challenging knowledge sources for large language models (LLMs) because they are hierarchical, multimodal, and densely connected through figures, tables, cross-references, and normative rules. Existing…
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GEMS-RAG: Graph-grounded Engineering Multimodal Standards Retrieval-Augmented Generation

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