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Autonomous agents driven by Large Language Models (LLMs) offer enormous potential for automation. Early proof of this technology can be found in various demonstrations of agents solving complex tasks, interacting with external systems to…

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

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

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

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

Smartphones have become indispensable in modern life, yet navigating complex tasks on mobile devices often remains frustrating. Recent advancements in large multimodal model (LMM)-based mobile agents have demonstrated the ability to…

Computation and Language · Computer Science 2025-01-29 Zhenhailong Wang , Haiyang Xu , Junyang Wang , Xi Zhang , Ming Yan , Ji Zhang , Fei Huang , Heng Ji

Recent advances in Vision-Language Models (VLMs) have enabled mobile agents to perceive and interact with real-world mobile environments based on human instructions. However, the current fully autonomous paradigm poses potential safety…

Artificial Intelligence · Computer Science 2026-04-28 Qihang Ai , Pi Bu , Yue Cao , Yingyao Wang , Jihao Gu , Jingxuan Xing , Zekun Zhu , Wei Jiang , Zhicheng Zheng , Jun Song , Yuning Jiang

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

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

Large language models (LLMs) have enabled remarkable advances in automated task-solving with multi-agent systems. However, most existing LLM-based multi-agent approaches rely on predefined agents to handle simple tasks, limiting the…

Artificial Intelligence · Computer Science 2024-05-01 Guangyao Chen , Siwei Dong , Yu Shu , Ge Zhang , Jaward Sesay , Börje F. Karlsson , Jie Fu , Yemin Shi

Large Language Model (LLM) agents significantly extend the capabilities of standalone LLMs, empowering them to interact with external tools (e.g., APIs, functions) and complete various tasks in a self-directed fashion. The challenge of tool…

Artificial Intelligence · Computer Science 2024-02-19 Weizhou Shen , Chenliang Li , Hongzhan Chen , Ming Yan , Xiaojun Quan , Hehong Chen , Ji Zhang , Fei Huang

Mobile agents are essential for automating tasks in complex and dynamic mobile environments. As foundation models evolve, the demands for agents that can adapt in real-time and process multimodal data have grown. This survey provides a…

Artificial Intelligence · Computer Science 2025-09-16 Biao Wu , Yanda Li , Zhiwei Zhang , Yunchao Wei , Meng Fang , Ling Chen

Large Language Models (LLMs) have achieved remarkable success across a wide array of tasks. Due to the impressive planning and reasoning abilities of LLMs, they have been used as autonomous agents to do many tasks automatically. Recently,…

Computation and Language · Computer Science 2024-04-22 Taicheng Guo , Xiuying Chen , Yaqi Wang , Ruidi Chang , Shichao Pei , Nitesh V. Chawla , Olaf Wiest , Xiangliang Zhang

Effort estimation is a crucial activity in agile software development, where teams collaboratively review, discuss, and estimate the effort required to complete user stories in a product backlog. Current practices in agile effort estimation…

Software Engineering · Computer Science 2025-09-19 Thanh-Long Bui , Hoa Khanh Dam , Rashina Hoda

Recent studies show that collaborating multiple large language model (LLM) powered agents is a promising way for task solving. However, current approaches are constrained by using a fixed number of agents and static communication…

Computation and Language · Computer Science 2024-11-18 Zijun Liu , Yanzhe Zhang , Peng Li , Yang Liu , Diyi Yang

Foundation models are becoming valuable tools in medicine. Yet despite their promise, the best way to leverage Large Language Models (LLMs) in complex medical tasks remains an open question. We introduce a novel multi-agent framework, named…

Computation and Language · Computer Science 2024-10-31 Yubin Kim , Chanwoo Park , Hyewon Jeong , Yik Siu Chan , Xuhai Xu , Daniel McDuff , Hyeonhoon Lee , Marzyeh Ghassemi , Cynthia Breazeal , Hae Won Park

Large language models (LLMs) demonstrate strong potential as agents for tool invocation due to their advanced comprehension and planning capabilities. Users increasingly rely on LLM-based agents to solve complex missions through iterative…

Artificial Intelligence · Computer Science 2025-04-17 Peijie Yu , Yifan Yang , Jinjian Li , Zelong Zhang , Haorui Wang , Xiao Feng , Feng Zhang

Significant advancements have occurred in the application of Large Language Models (LLMs) for social simulations. Despite this, their abilities to perform teaming in task-oriented social events are underexplored. Such capabilities are…

Artificial Intelligence · Computer Science 2025-08-18 Yuan Li , Lichao Sun , Yixuan Zhang

Autonomous agents powered by large language models (LLMs) have the potential to significantly enhance human productivity by reasoning, using tools, and executing complex tasks in diverse environments. However, current approaches to…

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…

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