WebNav：一种用于语音控制网页导航的智能代理
WebNav: An Intelligent Agent for Voice-Controlled Web Navigation
AI总结：
WebNav通过双重大语言模型架构结合视觉截图与动态DOM标记，将自然语言指令转化为精确的网页操作，实现了更智能的语音控制网页导航自动化。
摘要：
现代网页界面的当前状态，尤其是在面向无障碍使用方面，存在严重不足。传统的网页交互方法，如脚本语言和屏幕阅读器，往往缺乏处理动态内容的灵活性，也缺乏解释高层用户目标的智能。为了解决这些局限性，我们提出了WebNav，一种用于多模态网页导航的新型代理。WebNav采用双重大语言模型（LLM）架构，将自然语言命令转换为图形用户界面上精确、可执行的动作。该系统将来自截图的基于视觉的上下文与动态DOM标记浏览器扩展相结合，以稳健地识别可交互元素。一个高层的“控制器”LLM为用户的下一步目标制定策略，而第二个“助手”LLM生成执行所需的确切参数。这种关注点分离使得复杂的任务分解和动作制定成为可能。我们的工作展示了WebNav的完整架构和实现，展示了一种创建更智能的网页自动化代理的有前景的方法。
英文摘要：
The current state of modern web interfaces, especially in regards to accessibility focused usage is extremely lacking. Traditional methods for web interaction, such as scripting languages and screen readers, often lack the flexibility to handle dynamic content or the intelligence to interpret high-level user goals. To address these limitations, we introduce WebNav, a novel agent for multi-modal web navigation. WebNav leverages a dual Large Language Model (LLM) architecture to translate natural language commands into precise, executable actions on a graphical user interface. The system combines vision-based context from screenshots with a dynamic DOM-labeling browser extension to robustly identify interactive elements. A high-level 'Controller' LLM strategizes the next step toward a user's goal, while a second 'Assistant' LLM generates the exact parameters for execution. This separation of concerns allows for sophisticated task decomposition and action formulation. Our work presents the complete architecture and implementation of WebNav, demonstrating a promising approach to creating more intelligent web automation agents.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
