成像101：在科学计算成像上对大语言模型编码智能体进行基准测试

中文摘要 AI 辅助

计算成像从间接的、有噪声的测量中恢复隐藏信号，是跨学科定量发现的基础，但构建正确的重建管道需要深厚的领域专业知识，即使对于领域科学家来说也很费力。我们引入了Imaging-101，这是一个包含57个经过专家验证的计算成像任务的基准，涵盖六个科学领域，每个任务都基于一篇同行评审论文，并规范为标准化的四阶段管道（预处理、正向物理建模、逆求解器和可视化）。三个评估轨道（规划、功能级单元测试和端到端重建）在整个管道中探测不同的智能体能力。评估七个前沿大语言模型发现，将编码智能体应用于计算成像存在系统性挑战，这些挑战超出了一般编码基准所暴露的问题，包括算法选择、物理惯例处理和管道集成。这些发现突出了具体的能力差距，并指出技能增强、领域专业化的智能体是实现可靠计算成像辅助的实际途径。

英文摘要

Computational imaging, which recovers hidden signals from indirect, noisy measurements, underpins quantitative discovery across scientific disciplines, yet building a correct reconstruction pipeline demands deep domain expertise and remains laborious even for domain scientists. We introduce Imaging-101, a benchmark of 57 expert-verified computational imaging tasks spanning six scientific domains, each grounded in a peer-reviewed paper and canonicalized into a standardized four-stage pipeline (preprocessing, forward physics modeling, inverse solver, and visualization) Three evaluation tracks (planning, function-level unit tests, and end-to-end reconstruction) probe distinct agent capabilities across the full pipeline. Evaluating seven frontier LLMs uncovers systematic challenges in applying coding agents to computational imaging that go beyond those exposed by general coding benchmarks, spanning algorithm selection, physical convention handling, and pipeline integration. These findings highlight concrete capability gaps and point toward skill-augmented, domain-specialized agents as a practical path to reliable computational imaging assistance.

发表机构

• College of Future Technology and the National Biomedical Imaging Center, Peking University（北京大学未来技术学院和国家生物医学成像中心）
• AI for Science Institute (AISI)（科学人工智能研究所）
• University of Michigan（密歇根大学）
• State Key Laboratory of Acoustics and Marine Information, Institute of Acoustics, Chinese Academy of Sciences（中国科学院声学研究所声场声信息国家重点实验室）
• University of Chinese Academy of Sciences（中国科学院大学）
• School of Astronautics, Beihang University（北京航空航天大学宇航学院）
• Key Laboratory of Spacecraft Design Optimization and Dynamic Simulation Technologies, Ministry of Education（教育部航天器设计优化与动态仿真技术重点实验室）

机构由 AI 辅助整理，请以论文原文为准。