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arXiv · 2508.18689

AppAgent-Pro: A Proactive GUI Agent System for Multidomain Information Integration and User Assistance

Yuyang Zhao·Wentao Shi·Fuli Feng·Xiangnan He
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Abstract

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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Yuyang Zhao, Wentao Shi, Fuli Feng, Xiangnan He. 2025-08-26. AppAgent-Pro: A Proactive GUI Agent System for Multidomain Information Integration and User Assistance. https://doi.org/10.1145/3746252.3761473

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