CADWorld: Computer-Use Benchmark for Long-Horizon Computer-Aided Design
为解决现有基准对专业工程工作流程覆盖不足的问题，通过引入CADWorld基准来评估计算机使用代理在FreeCAD中长交互周期内的表现。
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Representative Papers
A Functional SVD Framework for Regularized Multivariate Functional PCA with Dual Penalization
本文提出了一种新的正则化多元函数主成分分析框架，通过函数奇异值分解实现对主成分及其得分的同时正则化，并引入稀疏惩罚提高解释性。
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Model Retirement Creates Reproducibility Risk in Biomedical AI Publications
研究针对生物医学AI论文因模型退役导致的可重复性风险问题，通过分析2022-2026年间的相关文献及模型生命周期数据提出解决方案。
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IDSPACE: A Novel Document Generator for Reliable Evaluation of Digital Identity Verification Systems [Extended Technical Report]
为解决数字身份验证系统评估难题，本文提出IDSpace文档生成器，通过模型引导贝叶斯优化、解耦用户指定元数据与自调参数及支持多种文档类型的方法，提高了评估一致性。
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Clinical Feasibility of Low-Magnification Fluorescence Imaging for Breast Cancer Margin Detection Using Texture Analysis and Deep Learning
This study addresses the clinical need for efficient and accurate intraoperative assessment of breast cancer margins, where high-magnification imaging is often limited by small field-of-view and slow acquisition. For the first time, it systematically compares 4× and 10× MUSE fluorescence imaging performance, integrating Local Binary Pattern (LBP) texture analysis with Vision Transformer (ViT)-based deep learning for tissue classification. Results demonstrate that 4× imaging achieves 96.30% sensitivity, 100% specificity, and 98.18% accuracy under the ViT model, while LBP yields consistent 96.67% accuracy across both magnifications. These findings indicate that low-magnification imaging can deliver diagnostic accuracy comparable to high-magnification approaches while substantially improving field-of-view coverage and imaging speed, thereby enhancing practicality in intraoperative settings.
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CADWorld: Computer-Use Benchmark for Long-Horizon Computer-Aided Design
为解决现有基准对专业工程工作流程覆盖不足的问题，通过引入CADWorld基准来评估计算机使用代理在FreeCAD中长交互周期内的表现。
0 citationsRead paper
A Functional SVD Framework for Regularized Multivariate Functional PCA with Dual Penalization
本文提出了一种新的正则化多元函数主成分分析框架，通过函数奇异值分解实现对主成分及其得分的同时正则化，并引入稀疏惩罚提高解释性。
0 citationsRead paper
Model Retirement Creates Reproducibility Risk in Biomedical AI Publications
研究针对生物医学AI论文因模型退役导致的可重复性风险问题，通过分析2022-2026年间的相关文献及模型生命周期数据提出解决方案。
0 citationsRead paper
IDSPACE: A Novel Document Generator for Reliable Evaluation of Digital Identity Verification Systems [Extended Technical Report]
为解决数字身份验证系统评估难题，本文提出IDSpace文档生成器，通过模型引导贝叶斯优化、解耦用户指定元数据与自调参数及支持多种文档类型的方法，提高了评估一致性。
0 citationsRead paper
Clinical Feasibility of Low-Magnification Fluorescence Imaging for Breast Cancer Margin Detection Using Texture Analysis and Deep Learning
This study addresses the clinical need for efficient and accurate intraoperative assessment of breast cancer margins, where high-magnification imaging is often limited by small field-of-view and slow acquisition. For the first time, it systematically compares 4× and 10× MUSE fluorescence imaging performance, integrating Local Binary Pattern (LBP) texture analysis with Vision Transformer (ViT)-based deep learning for tissue classification. Results demonstrate that 4× imaging achieves 96.30% sensitivity, 100% specificity, and 98.18% accuracy under the ViT model, while LBP yields consistent 96.67% accuracy across both magnifications. These findings indicate that low-magnification imaging can deliver diagnostic accuracy comparable to high-magnification approaches while substantially improving field-of-view coverage and imaging speed, thereby enhancing practicality in intraoperative settings.
0 citationsRead paper