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English(EN) 2d-fet-bench: from spatial reasoning to fet design on flakes

新基准测试AI设计复杂晶体管布局的能力

一个名为2D-FET-Bench V2的新基准已被开发出来,用于评估语言模型设计场效应晶体管(FET)布局的能力。该基准包含128个任务,每个任务提供来自二维薄膜显微图像的文本规格和轮廓坐标。系统以GDSII格式生成布局,然后验证其几何和结构正确性。在评估中,GPT5.6-Luna结合ReAct-3工作流,在任务上取得了62.3%的成功率,至少成功解决80.5%的任务,并在43.8%的尝试中表现出一致性。 AI

影响 该基准有望加速半导体制造和材料科学中由AI驱动的设计。

排序理由 该条目描述了一个新的基准和对特定科学/工程任务AI模型的评估,发布在arXiv上。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新基准测试AI设计复杂晶体管布局的能力

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该条目描述了一个新的基准和对特定科学/工程任务AI模型的评估,发布在arXiv上。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Dunzhi Zhou, Chengyu Zhu, Gang Qiu, Caiwen Ding ·

    2d-fet-bench:从空间推理到薄片上的FET设计

    arXiv:2610.07423v1 Announce Type: new Abstract: Field-effect transistor (FET) layouts on exfoliated two-dimensional flakes are typically drawn by hand for each flake, placing contacts and gates to match its position and outline in optical micrographs. To our knowledge, no executa…