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Recent advancements in large language models (LLMs) have led to the creation of intelligent agents capable of performing complex tasks. This paper introduces a novel LLM-based multimodal agent framework designed to operate smartphone…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Chi Zhang , Zhao Yang , Jiaxuan Liu , Yucheng Han , Xin Chen , Zebiao Huang , Bin Fu , Gang Yu

Mobile device agent based on Multimodal Large Language Models (MLLM) is becoming a popular application. In this paper, we introduce Mobile-Agent, an autonomous multi-modal mobile device agent. Mobile-Agent first leverages visual perception…

Computation and Language · Computer Science 2024-04-19 Junyang Wang , Haiyang Xu , Jiabo Ye , Ming Yan , Weizhou Shen , Ji Zhang , Fei Huang , Jitao Sang

AI agents using Large Language Models (LLMs) as foundations have shown promise in solving complex real-world tasks. In this paper, we propose an LLM-based agentic workflow for automating Standard Operating Procedures (SOP). For customer…

Human-Computer Interaction · Computer Science 2025-03-21 Mandar Kulkarni

Large language model (LLM)-based mobile agents are increasingly popular due to their capability to interact directly with mobile phone Graphic User Interfaces (GUIs) and their potential to autonomously manage daily tasks. Despite their…

Artificial Intelligence · Computer Science 2024-06-13 Luyuan Wang , Yongyu Deng , Yiwei Zha , Guodong Mao , Qinmin Wang , Tianchen Min , Wei Chen , Shoufa Chen

Large Language Model (LLM)-based mobile agents have made significant performance advancements. However, these agents often follow explicit user instructions while overlooking personalized needs, leading to significant limitations for real…

Computation and Language · Computer Science 2026-01-29 Shuoxin Wang , Chang Liu , Gowen Loo , Lifan Zheng , Kaiwen Wei , Xinyi Zeng , Jingyuan Zhang , Yu Tian

With the advancement of Multimodal Large Language Models (MLLM), LLM-driven visual agents are increasingly impacting software interfaces, particularly those with graphical user interfaces. This work introduces a novel LLM-based multimodal…

Human-Computer Interaction · Computer Science 2025-09-18 Yanda Li , Chi Zhang , Wenjia Jiang , Wanqi Yang , Bin Fu , Pei Cheng , Xin Chen , Ling Chen , Yunchao Wei

Recent advancements in Large Language Models (LLMs) have led to the development of intelligent LLM-based agents capable of interacting with graphical user interfaces (GUIs). These agents demonstrate strong reasoning and adaptability,…

Artificial Intelligence · Computer Science 2025-04-16 Wenjia Jiang , Yangyang Zhuang , Chenxi Song , Xu Yang , Joey Tianyi Zhou , Chi Zhang

Autonomous agents powered by large language models (LLMs) show promising potential in assistive tasks across various domains, including mobile device control. As these agents interact directly with personal information and device settings,…

Machine Learning · Computer Science 2026-01-28 Juyong Lee , Dongyoon Hahm , June Suk Choi , W. Bradley Knox , Kimin Lee

Recent advancements in multimodal large language models (MLLMs) have shown exceptional potential in enabling mobile-using agents to autonomously execute human instructions. However, fully automated agents often try to execute tasks even…

Computation and Language · Computer Science 2026-05-28 Zheng Wu , Pengzhou Cheng , Zongru Wu , Yuan Guo , Tianjie Ju , Aston Zhang , Gongshen Liu , Zhuosheng Zhang

With the rapid advancement of Vision-Language Models (VLMs), GUI-based mobile agents have emerged as a key development direction for intelligent mobile systems. However, existing agent models continue to face significant challenges in…

Multiagent Systems · Computer Science 2025-09-03 Cheng Zhang , Erhu Feng , Xi Zhao , Yisheng Zhao , Wangbo Gong , Jiahui Sun , Dong Du , Zhichao Hua , Yubin Xia , Haibo Chen

With the growing reliance on digital devices equipped with graphical user interfaces (GUIs), such as computers and smartphones, the need for effective automation tools has become increasingly important. While multimodal large language…

Human-Computer Interaction · Computer Science 2024-10-18 Jakub Hoscilowicz , Bartosz Maj , Bartosz Kozakiewicz , Oleksii Tymoshchuk , Artur Janicki

With the remarkable advancements of large language models (LLMs), LLM-based agents have become a research hotspot in human-computer interaction. However, there is a scarcity of benchmarks available for LLM-based mobile agents. Benchmarking…

Artificial Intelligence · Computer Science 2024-07-02 Shihan Deng , Weikai Xu , Hongda Sun , Wei Liu , Tao Tan , Jianfeng Liu , Ang Li , Jian Luan , Bin Wang , Rui Yan , Shuo Shang

Mobile GUI agents are becoming critical tools to improve user experience on smart devices, with multimodal large language models (MLLMs) emerging as the dominant paradigms in this domain. Current agents, however, rely on explicit human…

Human-Computer Interaction · Computer Science 2026-03-17 Qinglong Yang , Haoming Li , Haotian Zhao , Xiaokai Yan , Jingtao Ding , Fengli Xu , Yong Li

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…

Artificial Intelligence · Computer Science 2025-11-11 Yuyang Zhao , Wentao Shi , Fuli Feng , Xiangnan He

Large language models (LLMs) are being increasingly used for planning in orchestrated multi-agent systems. However, existing LLM-based approaches often fall short of human expectations and, critically, lack effective mechanisms for users to…

Human-Computer Interaction · Computer Science 2025-09-30 Hannah Kim , Kushan Mitra , Chen Shen , Dan Zhang , Estevam Hruschka

Vision language model (VLM)-based mobile agents show great potential for assisting users in performing instruction-driven tasks. However, these agents typically struggle with personalized instructions -- those containing ambiguous,…

Artificial Intelligence · Computer Science 2025-08-26 Xin Wang , Zhiyao Cui , Hao Li , Ya Zeng , Chenxu Wang , Ruiqi Song , Yihang Chen , Kun Shao , Qiaosheng Zhang , Jinzhuo Liu , Siyue Ren , Shuyue Hu , Zhen Wang

Web agents have emerged as a promising direction to automate Web task completion based on user instructions, significantly enhancing user experience. Recently, Web agents have evolved from traditional agents to Large Language Models…

Computation and Language · Computer Science 2025-03-25 Hongru Cai , Yongqi Li , Wenjie Wang , Fengbin Zhu , Xiaoyu Shen , Wenjie Li , Tat-Seng Chua

With the rapid rise of large language models (LLMs), phone automation has undergone transformative changes. This paper systematically reviews LLM-driven phone GUI agents, highlighting their evolution from script-based automation to…

The advancement of mobile GUI agents has opened new opportunities for automating tasks on mobile devices. Training these agents requires large-scale high-quality data, which is prohibitively expensive when relying on human labor. Given the…

Artificial Intelligence · Computer Science 2025-05-21 Wenhao Wang , Mengying Yuan , Zijie Yu , Guangyi Liu , Rui Ye , Tian Jin , Siheng Chen , Yanfeng Wang

Large language models (LLMs) and LLM-based agents are increasingly deployed as assistants in planning and decision making, yet most existing systems are implicitly optimized for a single-principal interaction paradigm, in which the model is…

Computation and Language · Computer Science 2026-04-29 Shu Yang , Shenzhe Zhu , Hao Zhu , José Ramón Enríquez , Di Wang , Alex Pentland , Michiel A. Bakker , Jiaxin Pei
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