让AI更可靠地自动化企业内网操作，解决执行不准、识别困难等痛点。
Cybernaut: Towards Reliable Web Automation
- 将用户操作转为稳定指令，提升任务可重复性。
- 在复杂界面中准确识别关键元素，成功率84.7%。
- 适合需要高可靠性的企业级网页自动化场景。
基于大语言模型的AI网页自动化虽具潜力，但在真实企业环境中面临四大挑战：执行一致性差、关键HTML元素识别不准、难以达到人类级精度，以及缺乏对内部系统的真实基准数据。现有方案多针对设计良好的公开网站（如Amazon.com、Apple.com），难以应对结构混乱的企业内网界面。为此，我们提出Cybernaut框架，实现面向企业级应用的高可靠性网页自动化。主要贡献包括：(1) 标准操作流程（SOP）生成器，将用户演示转化为适用于线性浏览任务的可靠自动化指令；(2) 针对复杂界面优化的高精度HTML DOM元素识别系统；(3) 量化评估执行一致性的新指标。在自建内部基准上的实证表明，相比browser_use，任务成功率达88.68%（提升23.2%，原为72%）。Cybernaut以84.7%准确率识别一致执行模式，支持实时信心评估与自适应引导，显著提升企业级自动化系统的可靠性，为未来研究奠定基础。
原文摘要 · Abstract (English)
The emergence of AI-driven web automation through Large Language Models (LLMs) offers unprecedented opportunities for optimizing digital workflows. However, deploying such systems within industry's real-world environments presents four core challenges: (1) ensuring consistent execution, (2) accurately identifying critical HTML elements, (3) meeting human-like accuracy in order to automate operations at scale and (4) the lack of comprehensive benchmarking data on internal web applications. Existing solutions are primarily tailored for well-designed, consumer-facing websites (e.g., Amazon.com, Apple.com) and fall short in addressing the complexity of poorly-designed internal web interfaces. To address these limitations, we present Cybernaut, a novel framework to ensure high execution consistency in web automation agents designed for robust enterprise use. Our contributions are threefold: (1) a Standard Operating Procedure (SOP) generator that converts user demonstrations into reliable automation instructions for linear browsing tasks, (2) a high-precision HTML DOM element recognition system tailored for the challenge of complex web interfaces, and (3) a quantitative metric to assess execution consistency. The empirical evaluation on our internal benchmark demonstrates that using our framework enables a 23.2% improvement (from 72% to 88.68%) in task execution success rate over the browser_use. Cybernaut identifies consistent execution patterns with 84.7% accuracy, enabling reliable confidence assessment and adaptive guidance during task execution in real-world systems. These results highlight Cybernaut's effectiveness in enterprise-scale web automation and lay a foundation for future advancements in web automation.
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