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IndustryCode: A Benchmark for Industry Code Generation
arXiv – CS AI|Puyu Zeng, Zhaoxi Wang, Zhixu Duan, Liang Feng, Shaobo Wang, Cunxiang Wang, Jinghang Wang, Bing Zhao, Hu Wei, Linfeng Zhang|
🤖AI Summary
Researchers introduce IndustryCode, the first comprehensive benchmark for evaluating Large Language Models' code generation capabilities across multiple industrial domains and programming languages. The benchmark includes 579 sub-problems from 125 industrial challenges spanning finance, automation, aerospace, and remote sensing, with the top-performing model Claude 4.5 Opus achieving 68.1% accuracy on sub-problems.
Key Takeaways
- →IndustryCode is the first multi-domain, multi-language benchmark for industrial code generation by LLMs.
- →The benchmark comprises 579 sub-problems derived from 125 primary industrial challenges across finance, automation, aerospace, and remote sensing.
- →It incorporates diverse programming languages including MATLAB, Python, C++, and Stata.
- →Claude 4.5 Opus achieved the highest performance with 68.1% accuracy on sub-problems and 42.5% on main problems.
- →The benchmark addresses gaps in existing evaluations that are limited to single domains and languages.
Mentioned in AI
Models
ClaudeAnthropic
#llm#code-generation#benchmark#industrial-ai#claude#programming#evaluation#machine-learning#automation
Read Original →via arXiv – CS AI
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