主动整合多领域信息，让AI助手提前预判用户需求。
AppAgent-Pro: A Proactive GUI Agent System for Multidomain Information Integration and User Assistance
- 基于用户指令主动跨域检索信息，非被动响应
- 支持深度多源信息挖掘，提升获取全面性
- 适合需要智能辅助决策的日常信息场景
基于大语言模型的智能体在处理复杂任务方面展现出显著能力，推动了更高级的信息检索，并支持更深入的人类信息探索行为。然而，现有大多数智能体仅以被动响应方式工作，严重限制其作为通用信息获取平台的有效性和效率。为此，本文提出AppAgent-Pro，一种主动式图形界面智能体系统，能够根据用户指令主动整合多领域信息。该方法使系统能主动预判用户的潜在需求，开展深层次的多领域信息挖掘，从而促进更全面、更智能的信息获取。AppAgent-Pro有望从根本上重新定义日常生活中的信息获取方式，对人类社会产生深远影响。代码已公开于：https://github.com/LaoKuiZe/AppAgent-Pro。演示视频可访问：https://www.dropbox.com/scl/fi/hvzqo5vnusg66srydzixo/AppAgent-Pro-demo-video.mp4?rlkey=o2nlfqgq6ihl125mcqg7bpgqu&st=d29vrzii&dl=0。
原文摘要 · Abstract (English)
Large language model (LLM)-based agents have demonstrated remarkable capabilities in addressing complex tasks, thereby enabling more advanced information retrieval and supporting deeper, more sophisticated human information-seeking behaviors. However, most existing agents operate in a purely reactive manner, responding passively to user instructions, which significantly constrains their effectiveness and efficiency as general-purpose platforms for information acquisition. To overcome this limitation, this paper proposes AppAgent-Pro, a proactive GUI agent system that actively integrates multi-domain information based on user instructions. This approach enables the system to proactively anticipate users' underlying needs and conduct in-depth multi-domain information mining, thereby facilitating the acquisition of more comprehensive and intelligent information. AppAgent-Pro has the potential to fundamentally redefine information acquisition in daily life, leading to a profound impact on human society. Our code is available at: https://github.com/LaoKuiZe/AppAgent-Pro. The demonstration video could be found at: https://www.dropbox.com/scl/fi/hvzqo5vnusg66srydzixo/AppAgent-Pro-demo-video.mp4?rlkey=o2nlfqgq6ihl125mcqg7bpgqu&st=d29vrzii&dl=0.
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