新框架使用少样本学习校准 Bosch 蚀刻模拟器

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

研究人员开发了一个新颖的框架，使用有限数量的真实世界测量数据来校准 Bosch 蚀刻模拟器。这种少样本方法将模拟器参数与直接工艺变量解耦，从而能够推断出特定配方的模拟器参数。该系统结合了局部探索、LLM 引导的候选生成和基于 XGBoost 的代理筛选，以有效地搜索参数空间，在保留的条件下实现蚀刻深度和侧壁角度的准确预测。 AI

影响该框架通过实现更好的模拟器校准，有可能提高半导体制造过程的准确性和效率。

排序理由该集群包含一篇详细介绍新技术框架和实验结果的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

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

本文如何被排名

Signal score: 6 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群包含一篇详细介绍新技术框架和实验结果的研究论文。[lever_c_demoted from research: ic=1 ai=0.7]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, infra; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Same-day; Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Xinyu Jia, Jainil Shah, Rahul Tripathi, Vijay Gupta, Zhihong Chen · 2026-10-27 04:00

博世蚀刻模拟器的实景到模拟校准，采用少样本XSEM数据和混合搜索

arXiv:2610.31904v1 Announce Type: cross Abstract: The Bosch process is widely used in MEMS and TSV fabrication, but accurate prediction of etching outcomes remains difficult without calibration against real measurements, which are sparse and costly to obtain. This work presents a…

本文如何被排名

报道来源 [1]

博世蚀刻模拟器的实景到模拟校准，采用少样本XSEM数据和混合搜索

相关实体

相关话题