DrafterBench：面向土木工程任务自动化的大型语言模型基准测试

DrafterBench: Benchmarking Large Language Models for Tasks Automation in Civil Engineering

July 15, 2025

作者: Yinsheng Li, Zhen Dong, Yi Shao

cs.AI

摘要

大型语言模型（LLM）代理在解决现实世界问题方面展现出巨大潜力，并有望成为工业任务自动化的解决方案。然而，从工业视角（如土木工程领域）系统评估自动化代理仍需更多基准测试。为此，我们提出了DrafterBench，用于在技术图纸修订这一土木工程代表性任务背景下全面评估LLM代理。DrafterBench包含从实际图纸文件中总结出的十二类任务，配备46项定制功能/工具，共计1920项任务。作为一个开源基准，DrafterBench严格测试AI代理在解读复杂且长上下文指令、利用先验知识以及通过隐式策略意识适应动态指令质量方面的熟练程度。该工具包全面评估了结构化数据理解、功能执行、指令遵循及批判性推理等多项能力。DrafterBench提供任务准确率与错误统计的详细分析，旨在深入洞察代理能力，并为LLM在工程应用中的集成指明改进方向。我们的基准测试平台可在https://github.com/Eason-Li-AIS/DrafterBench获取，测试集托管于https://huggingface.co/datasets/Eason666/DrafterBench。

English

Large Language Model (LLM) agents have shown great potential for solving real-world problems and promise to be a solution for tasks automation in industry. However, more benchmarks are needed to systematically evaluate automation agents from an industrial perspective, for example, in Civil Engineering. Therefore, we propose DrafterBench for the comprehensive evaluation of LLM agents in the context of technical drawing revision, a representation task in civil engineering. DrafterBench contains twelve types of tasks summarized from real-world drawing files, with 46 customized functions/tools and 1920 tasks in total. DrafterBench is an open-source benchmark to rigorously test AI agents' proficiency in interpreting intricate and long-context instructions, leveraging prior knowledge, and adapting to dynamic instruction quality via implicit policy awareness. The toolkit comprehensively assesses distinct capabilities in structured data comprehension, function execution, instruction following, and critical reasoning. DrafterBench offers detailed analysis of task accuracy and error statistics, aiming to provide deeper insight into agent capabilities and identify improvement targets for integrating LLMs in engineering applications. Our benchmark is available at https://github.com/Eason-Li-AIS/DrafterBench, with the test set hosted at https://huggingface.co/datasets/Eason666/DrafterBench.