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GUI agents drive applications through their visual interfaces instead of programmatic APIs, interacting with arbitrary software via taps, swipes, and keystrokes, reaching a long tail of applications that CLI-based agents cannot. Yet…

Machine Learning · Computer Science 2026-04-14 Fei Tang , Zhiqiong Lu , Boxuan Zhang , Weiming Lu , Jun Xiao , Yueting Zhuang , Yongliang Shen

Large Language Models (LLMs) show promise as data analysis agents, but existing benchmarks overlook the iterative nature of the field, where experts' decisions evolve with deeper insights of the dataset. To address this, we introduce…

Computation and Language · Computer Science 2025-06-09 Hanyu Li , Haoyu Liu , Tingyu Zhu , Tianyu Guo , Zeyu Zheng , Xiaotie Deng , Michael I. Jordan

The advent of Multimodal LLMs has significantly enhanced image OCR recognition capabilities, making GUI automation a viable reality for increasing efficiency in digital tasks. One fundamental aspect of developing a GUI automation system is…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Qinchen Wu , Difei Gao , Kevin Qinghong Lin , Zhuoyu Wu , Xiangwu Guo , Peiran Li , Weichen Zhang , Hengxu Wang , Mike Zheng Shou

Large Language Model (LLM) agents are increasingly applied to engineering design tasks, yet existing evaluation frameworks do not adequately address multi-agent systems that combine simulation, retrieval, and manufacturing preparation. We…

Artificial Intelligence · Computer Science 2026-05-28 Gioele Molinari , Florian Felten , Soheyl Massoudi , Mark Fuge

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

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

The recent progress of large language model agents has opened new possibilities for automating tasks through graphical user interfaces (GUIs), especially in mobile environments where intelligent interaction can greatly enhance usability.…

Multimodal Large Language Models (MLLMs) are evolving from passive observers into active agents, solving problems through Visual Expansion (invoking visual tools) and Knowledge Expansion (open-web search). However, existing evaluations fall…

Artificial Intelligence · Computer Science 2026-04-06 Qianshan Wei , Yishan Yang , Siyi Wang , Jinglin Chen , Binyu Wang , Jiaming Wang , Shuang Chen , Zechen Li , Yang Shi , Yuqi Tang , Weining Wang , Yi Yu , Chaoyou Fu , Qi Li , Yi-Fan Zhang

User interface (UI) design is an iterative process in which designers progressively refine their work with design software such as Figma or Sketch. Recent advances in vision language models (VLMs) with tool invocation suggest these models…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Daeheon Jeong , Seoyeon Byun , Kihoon Son , Dae Hyun Kim , Juho Kim

Graphical User Interface (GUI) agents have gained substantial attention due to their impressive capabilities to complete tasks through multiple interactions within GUI environments. However, existing agents primarily focus on enhancing the…

Computation and Language · Computer Science 2025-05-28 Qinzhuo Wu , Pengzhi Gao , Wei Liu , Jian Luan

Multimodal large language models (MLLMs) are transforming the capabilities of graphical user interface (GUI) agents, facilitating their transition from controlled simulations to complex, real-world applications across various platforms.…

Artificial Intelligence · Computer Science 2025-06-18 Boyu Gou , Ruohan Wang , Boyuan Zheng , Yanan Xie , Cheng Chang , Yiheng Shu , Huan Sun , Yu Su

Graphical User Interface (GUI) agents show great potential for enabling foundation models to complete real-world tasks, revolutionizing human-computer interaction and improving human productivity. In this report, we present OmegaUse, a…

Multimodal large language models (MLLMs) have markedly expanded the competence of graphical user-interface (GUI) systems, propelling them beyond controlled simulations into complex, real-world environments across diverse platforms. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Bin Lei , Nuo Xu , Ali Payani , Mingyi Hong , Chunhua Liao , Yu Cao , Caiwen Ding

Large Language Model (LLM) agents have shown great potential for solving real-world problems and promise to be a solution for tasks automation in industry. However, more benchmarks are needed to systematically evaluate automation agents…

Artificial Intelligence · Computer Science 2025-07-16 Yinsheng Li , Zhen Dong , Yi Shao

The demand for quality in mobile applications has increased greatly given users' high reliance on them for daily tasks. Developers work tirelessly to ensure that their applications are both functional and user-friendly. In pursuit of this,…

Software Engineering · Computer Science 2025-05-16 Safwat Ali Khan

Graphical User Interface (GUI) agents have made significant progress in automating digital tasks through the utilization of computer vision and language models. Nevertheless, existing agent systems encounter notable limitations. Firstly,…

Artificial Intelligence · Computer Science 2025-06-24 Jinjie Wei , Jiyao Liu , Lihao Liu , Ming Hu , Junzhi Ning , Mingcheng Li , Weijie Yin , Junjun He , Xiao Liang , Chao Feng , Dingkang Yang

Large Language Models (LLMs) based autonomous agents demonstrate multifaceted capabilities to contribute substantially to economic production. However, existing benchmarks remain focused on single agentic capability, failing to capture…

Artificial Intelligence · Computer Science 2026-04-24 Keyu Li , Junhao Shi , Yang Xiao , Mohan Jiang , Jie Sun , Yunze Wu , Dayuan Fu , Shijie Xia , Xiaojie Cai , Tianze Xu , Weiye Si , Wenjie Li , Dequan Wang , Pengfei Liu

AI-powered web agents have the potential to automate repetitive tasks, such as form filling, information retrieval, and scheduling, but they struggle to reliably execute these tasks without human intervention, requiring users to provide…

Human-Computer Interaction · Computer Science 2026-01-27 Yimeng Liu , Misha Sra , Jeevana Priya Inala , Chenglong Wang

GUI agents powered by vision-language models (VLMs) show promise in automating complex digital tasks. However, their effectiveness in real-world applications is often limited by scarce training data and the inherent complexity of these…

Computation and Language · Computer Science 2025-09-30 Ran Xu , Kaixin Ma , Wenhao Yu , Hongming Zhang , Joyce C. Ho , Carl Yang , Dong Yu

The realization of Artificial General Intelligence (AGI) necessitates Embodied AI agents capable of robust spatial perception, effective task planning, and adaptive execution in physical environments. However, current large language models…

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