UFO2: The Desktop AgentOS
Not on the map. Why?
Cited by 26 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
Recent Computer-Using Agents (CUAs), powered by multimodal large language models (LLMs), offer a promising direction for automating complex desktop workflows through natural language. However, most existing CUAs remain conceptual prototypes, hindered by shallow OS integration, fragile screenshot-based interaction, and disruptive execution. We present UFO2, a multiagent AgentOS for Windows desktops that elevates CUAs into practical, system-level automation. UFO2 features a centralized HostAgent for task decomposition and coordination, alongside a collection of application-specialized AppAgent equipped with native APIs, domain-specific knowledge, and a unified GUI--API action layer. This architecture enables robust task execution while preserving modularity and extensibility. A hybrid control detection pipeline fuses Windows UI Automation (UIA) with vision-based parsing to support diverse interface styles. Runtime efficiency is further enhanced through speculative multi-action planning, reducing per-step LLM overhead. Finally, a Picture-in-Picture (PiP) interface enables automation within an isolated virtual desktop, allowing agents and users to operate concurrently without interference. We evaluate UFO2 across over 20 real-world Windows applications, demonstrating substantial improvements in robustness and execution accuracy over prior CUAs. Our results show that deep OS integration unlocks a scalable path toward reliable, user-aligned desktop automation.
Key facts. Cited by 41 papers in the map (data through 14 Oct 2026). Builds on 39 of its 59 references that are in the map. First posted on arXiv 20 Apr 2025.
Builds on
39 of 59 references.
References · 39
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2023A Survey of Large Language Modelscited by 2,576
- 2023A Survey on Large Language Model based Autonomous Agentscited by 2,242
- 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
- 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,434
- 2023CogVLM: Visual Expert for Pretrained Language Modelscited by 708
- 2023CogAgent: A Visual Language Model for GUI Agentscited by 704
- 2023The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)cited by 681
- 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 634
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- 2024Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agentscited by 382
- 2023Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4Vcited by 299
- 2024MM-LLMs: Recent Advances in MultiModal Large Language Modelscited by 278
- 2024Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scalecited by 223
- 2024OmniParser for Pure Vision Based GUI Agentcited by 198
- 2024Agent S: An Open Agentic Framework that Uses Computers Like a Humancited by 187
- 2025UI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learningcited by 168
- 2024Large Language Model-Brained GUI Agents: A Surveycited by 162
- 2024UFO: A UI-Focused Agent for Windows OS Interactioncited by 148
- 2024ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agentscited by 133
- 2024LLM Multi-Agent Systems: Challenges and Open Problemscited by 120
- 2024ScreenAgent: A Vision Language Model-driven Computer Control Agentcited by 102
- 2024AIOS: LLM Agent Operating Systemcited by 97
- 2023Real-Time Flying Object Detection with YOLOv8cited by 94
- 2023TaskWeaver: A Code-First Agent Frameworkcited by 86
- 2024Beyond Browsing: API-Based Web Agentscited by 78
- 2024Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluationcited by 75
- 2023Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generationcited by 74
- 2024In-context Learning with Retrieved Demonstrations for Language Models: A Surveycited by 70
- 2023LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystemcited by 38
- 2024Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detectioncited by 29
- 2025API Agents vs. GUI Agents: Divergence and Convergencecited by 29
- 2023Xpert: Empowering Incident Management with Query Recommendations via Large Language Modelscited by 22
- 2024AllHands: Ask Me Anything on Large-scale Verbatim Feedback via Large Language Modelscited by 6
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Citing papers per year: 2025: 19; 2026: 22.
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- 2026Model-Native Computing Architecture: Envisioning Future System Architecture Through the Lens of Computer Architecturecited by 2
- 2026CORPGEN: Simulating Corporate Environments with Autonomous Digital Employees in Multi-Horizon Task Environmentscited by 1
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- 2026MissClick: Execution-Aware Adversarial Attacks on Coordinate Generation in GUI Grounding Models4 Aug 2026
- 2026StateAct: Program State, before Pixels, for Long-Horizon Computer-Use Agents24 Jul 2026
- 2026OctoNest: Adaptive Cross-Device Execution through Stateful Control18 Jun 2026
- 2026From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI12 Jun 2026
- 2026Model-Native Computing Architecture: Envisioning Future System Architecture Through the Lens of Computer Architecture29 May 2026
- 2026CORPGEN: Simulating Corporate Environments with Autonomous Digital Employees in Multi-Horizon Task Environments15 Feb 2026
- 2025D2E: Scaling Vision-Action Pretraining on Desktop Data for Transfer to Embodied AI7 Oct 2025
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