粒子物理学家和蒙特卡洛生成器开发者终于有了自动化工具来填补Rivet例程缺口，建议做高能物理分析或模型验证的团队关注，能大幅节省手动编写例程的时间。
粒子物理对撞机实验依赖Rivet例程来比较新理论模型与测量数据，但目前仅有39%的测量有公开例程。AgentRivet是一个基于大语言模型的自动化工作流，能从期刊论文中提取物理分析信息并生成缺失的Rivet例程。系统包含多步骤流程，中间有代码和物理审查作为质量控制。测试使用OpenAI、Anthropic和Google的商业模型，针对ATLAS和CMS实验的两项最新测量，生成了语法错误少、物理保真度合理的例程。主要问题源于论文中模糊的定义，部分模型在实现复杂观测量时仍有困难。
AgentRivet: an automated system for producing Rivet routines from journal publications
Particle physics collider experiments provide Rivet routines as part of the analysis preservation strategy for model-independent measurements. Rivet is a C++ toolkit that allow new theoretical models to be compared to the measurements, thus aiding the development and tuning of Monte Carlo event generators as well as searches for physics beyond the Standard Model. However, analysis coverage is known to be incomplete, with only 39% of measurements having documented and publicly available Rivet routines. In this article, we design and implement an automated workflow based on Large Language Models with the goal of providing the missing routines. This multi-step workflow, referred to as AgentRivet, extracts the physics analysis information from published papers and writes the missing Rivet routines, with intermediate code- and physics- reviews as part of an autonomous quality control. We report the results obtained using commercial Large Language Models, provided by OpenAI, Anthropic, and Google, for two recent measurements from the ATLAS and CMS experiments. We find that AgentRivet produces competent Rivet routines with few syntax errors. The physics fidelity of the routines is reasonable and follows the explanations given in the relevant publications. Nevertheless, physics-implementation issues do arise and are investigated using the artefacts produced by AgentRivet. The majority of physics implementation issues arise from subtle-but-ambiguous definitions in the given publication, although some models struggle to implement complex observables even when clear definitions are given.