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New OmniRouting benchmark tests LLMs on complex PCB routing tasks

Researchers have introduced OmniRouting, a new benchmark designed to test the spatial reasoning capabilities of large language models (LLMs) in the complex domain of printed circuit board (PCB) routing. The benchmark includes over 1,600 industrial-grade PCB designs and four distinct tasks focusing on geometric, design-rule, and electrical functionality constraints. Initial evaluations indicate that current multimodal LLMs exhibit significant limitations in path planning, constraint adherence, and maintaining electrical correctness for PCB routing. AI

IMPACT This benchmark could accelerate the development of LLMs capable of complex spatial and constraint-based reasoning, potentially impacting fields like electronic design automation.

RANK_REASON The cluster describes a new academic benchmark for evaluating LLMs on a specific technical task, published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New OmniRouting benchmark tests LLMs on complex PCB routing tasks

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The cluster describes a new academic benchmark for evaluating LLMs on a specific technical task, published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Taiting Lu, Kaiyuan Lin, Ziwei Dong, Sisong Bei, Haolin Ye, Yuxin Tian, Runze Liu, Mingjia Wang, Jingying Zeng, Hongxing Pan, Kai Zhang, Haoyu Wang, Guoliang Shi, Ling Ma, Yifan Yang, Jiaying Lu, Qi He, Yi-Chao Chen, Sung-Liang Chen, Yincheng Jin, Mahant… ·

    OmniRouting: A Semantic-Coupled Multimodal Benchmark for Constraint-Aware Spatial Reasoning in PCB Routing

    arXiv:2608.04434v1 Announce Type: new Abstract: Recent large language models (LLMs) have demonstrated remarkable progress in constraint-aware navigation, maze reasoning, and graph reasoning. However, their ability to reason about complex routing problems under strict geometric, t…