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Symbol and Footprint Database for Electronic Components by Agentic Recognition and Generation

Research LLM Agents

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TL;DR - SFgen uses multimodal LLM agents to recognize and generate PCB component symbols and footprints, reducing reliance on error-prone manual library creation. It also powers SFnet, an expanding database currently covering 1,000 components.

  • SFgen reports 86% accuracy for symbol generation.
  • Footprint generation achieves 80% accuracy.
  • The resulting SFnet database supports future automated PCB design generation.

Sources (1)

Symbol and Footprint Database for Electronic Components by Agentic Recognition and Generation

arXiv cs.AI Yichen Shi, Yuzhi Liu, Zhuofu Tao, Li Huang, Yuhao Gao, Ting-Jung Lin, Lei Hel 2026-07-22 arXiv:2607.19767
Public signals Semantic Scholar citations 0 · Semantic Scholar influential citations 0
Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · Citations 0 · Influential citations 0 X · N/A Fetched 2026-08-12 14:32:21.370786 UTC

TL;DR - SFgen uses multimodal LLM agents to recognize and generate PCB component symbols and footprints, reducing reliance on error-prone manual library creation. It also powers SFnet, an expanding database currently covering 1,000 components.

  • SFgen reports 86% accuracy for symbol generation.
  • Footprint generation achieves 80% accuracy.
  • The resulting SFnet database supports future automated PCB design generation.
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