@article{Li2026, 
author = {Shasha Li and Bin Ji and Xiaodong Liu and Jun Ma and Jie Yu},
title = {ComAlign: A Benchmark Aligning Natural Language with Operating System Commands},
year = {2026},
journal = {Computers, Materials & Continua},
volume = {87},
number = {2},
pages = {54},
keywords = {Large language model, language-command alignment, artificial intelligence operating system},
url = {https://www.sciopen.com/article/10.32604/cmc.2026.076083},
doi = {10.32604/cmc.2026.076083},
abstract = {Aligning natural language with operating system (OS) commands allows users to perform complex computer tasks through simple natural language descriptions. However, due to the complex nature of natural language, it still remains challenging to achieve precise alignment. In this paper, we present ComAlign, a Chinese benchmark dataset that pairs Chinese natural language descriptions with corresponding OS commands. ComAlign covers a broad range of  82 distinct OS command types with a total of  1811 natural language descriptions. We elaborate on the construction of ComAlign and construct three baselines to evaluate the alignment accuracy on ComAlign. Experimental results show that even advanced large language models struggle with certain ambiguously phrased OS commands. Specifically, the best performing baseline achieves 46.9% alignment accuracy. We demonstrate that ComAlign is collected from real-world application scenarios, making it particularly suitable for developing and benchmarking intelligent OS and agent systems that support user-machine interactions through natural language.}
}