{"ID":2877912,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.18689","arxiv_id":"2508.18689","title":"AppAgent-Pro: A Proactive GUI Agent System for Multidomain Information Integration and User Assistance","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\u0026st=d29vrzii\u0026dl=0.","short_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...","url_abs":"https://arxiv.org/abs/2508.18689","url_pdf":"https://arxiv.org/pdf/2508.18689v2","authors":"[\"Yuyang Zhao\",\"Wentao Shi\",\"Fuli Feng\",\"Xiangnan He\"]","published":"2025-08-26T05:23:24Z","proceeding":"cs.AI","tasks":"[\"cs.AI\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false,"code_links":[{"ID":610427,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2877912,"paper_url":"https://arxiv.org/abs/2508.18689","paper_title":"AppAgent-Pro: A Proactive GUI Agent System for Multidomain Information Integration and User Assistance","repo_url":"https://github.com/LaoKuiZe/AppAgent-Pro","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}