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【第72期】LLM-Brained GUI Agents: A Survey
Seventy3: 用NotebookLM将论文生成播客，让大家跟着AI一起进步。
今天的主题是：Large Language Model-Brained GUI Agents: A SurveySummary
This paper surveys the development and application of Large Language Model (LLM)-powered Graphical User Interface (GUI) agents for automating tasks across various platforms (web, mobile, desktop). It examines the evolution of GUI automation from rule-based systems to intelligent agents leveraging LLMs, computer vision, and reinforcement learning. The authors detail the architecture and workflow of these agents, including prompt engineering, model inference, action execution, and memory management. Finally, the paper explores datasets for optimizing LLMs for GUI tasks, evaluation metrics and benchmarks for assessing agent performance, and the challenges and future directions of this field, including safety, reliability, and ethical considerations.
原文链接：https://arxiv.org/abs/2411.18279
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By 任雨山Seventy3: 用NotebookLM将论文生成播客，让大家跟着AI一起进步。
今天的主题是：Large Language Model-Brained GUI Agents: A SurveySummary
This paper surveys the development and application of Large Language Model (LLM)-powered Graphical User Interface (GUI) agents for automating tasks across various platforms (web, mobile, desktop). It examines the evolution of GUI automation from rule-based systems to intelligent agents leveraging LLMs, computer vision, and reinforcement learning. The authors detail the architecture and workflow of these agents, including prompt engineering, model inference, action execution, and memory management. Finally, the paper explores datasets for optimizing LLMs for GUI tasks, evaluation metrics and benchmarks for assessing agent performance, and the challenges and future directions of this field, including safety, reliability, and ethical considerations.
原文链接：https://arxiv.org/abs/2411.18279