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Graphical User Interface (GUI) agents show amazing abilities in assisting human-computer interaction, automating human user's navigation on digital devices. An ideal GUI agent is expected to achieve high accuracy, low latency, and…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Zhiyuan Huang , Ziming Cheng , Junting Pan , Zhaohui Hou , Mingjie Zhan

The development of autonomous agents for graphical user interfaces (GUIs) presents major challenges in artificial intelligence. While recent advances in native agent models have shown promise by unifying perception, reasoning, action, and…

Artificial Intelligence · Computer Science 2025-09-08 Haoming Wang , Haoyang Zou , Huatong Song , Jiazhan Feng , Junjie Fang , Junting Lu , Longxiang Liu , Qinyu Luo , Shihao Liang , Shijue Huang , Wanjun Zhong , Yining Ye , Yujia Qin , Yuwen Xiong , Yuxin Song , Zhiyong Wu , Aoyan Li , Bo Li , Chen Dun , Chong Liu , Daoguang Zan , Fuxing Leng , Hanbin Wang , Hao Yu , Haobin Chen , Hongyi Guo , Jing Su , Jingjia Huang , Kai Shen , Kaiyu Shi , Lin Yan , Peiyao Zhao , Pengfei Liu , Qinghao Ye , Renjie Zheng , Shulin Xin , Wayne Xin Zhao , Wen Heng , Wenhao Huang , Wenqian Wang , Xiaobo Qin , Yi Lin , Youbin Wu , Zehui Chen , Zihao Wang , Baoquan Zhong , Xinchun Zhang , Xujing Li , Yuanfan Li , Zhongkai Zhao , Chengquan Jiang , Faming Wu , Haotian Zhou , Jinlin Pang , Li Han , Qi Liu , Qianli Ma , Siyao Liu , Songhua Cai , Wenqi Fu , Xin Liu , Yaohui Wang , Zhi Zhang , Bo Zhou , Guoliang Li , Jiajun Shi , Jiale Yang , Jie Tang , Li Li , Qihua Han , Taoran Lu , Woyu Lin , Xiaokang Tong , Xinyao Li , Yichi Zhang , Yu Miao , Zhengxuan Jiang , Zili Li , Ziyuan Zhao , Chenxin Li , Dehua Ma , Feng Lin , Ge Zhang , Haihua Yang , Hangyu Guo , Hongda Zhu , Jiaheng Liu , Junda Du , Kai Cai , Kuanye Li , Lichen Yuan , Meilan Han , Minchao Wang , Shuyue Guo , Tianhao Cheng , Xiaobo Ma , Xiaojun Xiao , Xiaolong Huang , Xinjie Chen , Yidi Du , Yilin Chen , Yiwen Wang , Zhaojian Li , Zhenzhu Yang , Zhiyuan Zeng , Chaolin Jin , Chen Li , Hao Chen , Haoli Chen , Jian Chen , Qinghao Zhao , Guang Shi

Recent advancements in image generation models have enabled the prediction of future Graphical User Interface (GUI) states based on user instructions. However, existing benchmarks primarily focus on general domain visual fidelity, leaving…

This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e.g., keyboard and mouse operations). Unlike prevailing agent frameworks that depend on heavily…

Computer use agents automate digital tasks by directly interacting with graphical user interfaces (GUIs) on computers and mobile devices, offering significant potential to enhance human productivity by completing an open-ended space of user…

Artificial Intelligence · Computer Science 2025-04-02 Saaket Agashe , Kyle Wong , Vincent Tu , Jiachen Yang , Ang Li , Xin Eric Wang

Recent advances in multimodal large language models have driven growing interest in graphical user interface (GUI) agents, yet their generalization remains constrained by the scarcity of large-scale training data spanning diverse real-world…

Computation and Language · Computer Science 2026-05-15 Weimin Xiong , Shuhao Gu , Bowen Ye , Zihao Yue , Lei Li , Feifan Song , Sujian Li , Hao Tian

Graphical user interface (GUI) agents have advanced rapidly but still struggle with complex tasks involving novel UI elements, long-horizon actions, and personalized trajectories. In this work, we introduce Instruction Agent, a GUI agent…

Artificial Intelligence · Computer Science 2025-09-10 Yinheng Li , Hailey Hultquist , Justin Wagle , Kazuhito Koishida

This paper presents MagicGUI, a foundational mobile GUI agent designed to address critical challenges in perception, grounding, and reasoning within real-world mobile GUI environments. The framework is underpinned by following six key…

Autonomous agents that control computer interfaces to accomplish human tasks are emerging. Leveraging LLMs to power such agents has been of special interest, but unless fine-tuned on human-collected task demonstrations, performance is still…

Artificial Intelligence · Computer Science 2024-11-14 Wei Li , William Bishop , Alice Li , Chris Rawles , Folawiyo Campbell-Ajala , Divya Tyamagundlu , Oriana Riva

With the widespread adoption of Graphical User Interface (GUI) agents for automating GUI interaction tasks, substantial research focused on improving GUI perception to ground task instructions into concrete action steps. However, the step…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Xuan Wang , Siyuan Su , Quantong Fu , Yongxiang Hu , Yangfan Zhou

The integration of Generative AI models into AI-native network systems offers a transformative path toward achieving autonomous and adaptive control. However, the application of such models to continuous control tasks is impeded by…

Artificial Intelligence · Computer Science 2026-03-12 Yuanhao Li , Haozhe Wang , Geyong Min , Nektarios Georgalas , Wang Miao

With the development of multimodal reasoning models, Computer Use Agents (CUAs), akin to Jarvis from \textit{"Iron Man"}, are becoming a reality. GUI grounding is a core component for CUAs to execute actual actions, similar to mechanical…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Miaosen Zhang , Ziqiang Xu , Jialiang Zhu , Qi Dai , Kai Qiu , Yifan Yang , Chong Luo , Tianyi Chen , Justin Wagle , Tim Franklin , Baining Guo

GUI grounding is a critical capability for vision-language models (VLMs) that enables automated interaction with graphical user interfaces by locating target elements from natural language instructions. However, grounding on GUI screenshots…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Siqi Pei , Liang Tang , Tiaonan Duan , Long Chen , Shuxian Li , Kaer Huang , Yanzhe Jing , Yiqiang Yan , Bo Zhang , Chenghao Jiang , Borui Zhang , Jiwen Lu

Graphical User Interface (GUI) agents are autonomous systems that interpret and generate actions, enabling intelligent user assistance and automation. Effective training of these agent presents unique challenges, such as sparsity in…

Computation and Language · Computer Science 2025-03-28 Yiqiao Jin , Stefano Petrangeli , Yu Shen , Gang Wu

Much of the previous work towards digital agents for graphical user interfaces (GUIs) has relied on text-based representations (derived from HTML or other structured data sources), which are not always readily available. These input…

With the deep integration of artificial intelligence and interactive technology, Graphical User Interface (GUI) Agent, as the carrier connecting goal-oriented natural language and real-world devices, has received widespread attention from…

Artificial Intelligence · Computer Science 2025-11-13 Leyang Yang , Ziwei Wang , Xiaoxuan Tang , Sheng Zhou , Dajun Chen , Wei Jiang , Yong Li

We introduce GUI-360$^\circ$, a large-scale, comprehensive dataset and benchmark suite designed to advance computer-using agents (CUAs). CUAs present unique challenges and is constrained by three persistent gaps: a scarcity of real-world…

LLM-based agents can autonomously accomplish complex tasks across various domains. However, to further cultivate capabilities such as adaptive behavior and long-term decision-making, training on static datasets built from human-level…

Machine Learning · Computer Science 2025-12-24 Yuchen Huang , Sijia Li , Minghao Liu , Wei Liu , Shijue Huang , Zhiyuan Fan , Hou Pong Chan , Yi R. Fung

Graphical User Interface (GUI) agents possess significant commercial and social value, and GUI agents powered by advanced multimodal large language models (MLLMs) have demonstrated remarkable potential. Currently, existing GUI agents…

Artificial Intelligence · Computer Science 2025-09-05 Weizhi Chen , Ziwei Wang , Leyang Yang , Sheng Zhou , Xiaoxuan Tang , Jiajun Bu , Yong Li , Wei Jiang

Visual grounding is the task of localising image regions from natural language queries and is critical for reasoning capable Graphical User Interface agents. Many existing methods rely on massive, noisy synthetic datasets. This work…

Artificial Intelligence · Computer Science 2025-11-17 Georgios Pantazopoulos , Eda B. Özyiğit