OS-ATLAS: A Foundation Action Model for Generalist GUI Agents
On the map: Multimodal LLMs / vision-language models → Embodied and 3D vision-language models
also in 1 more
Abstract (arXiv)
Existing efforts in building GUI agents heavily rely on the availability of robust commercial Vision-Language Models (VLMs) such as GPT-4o and GeminiProVision. Practitioners are often reluctant to use open-source VLMs due to their significant performance lag compared to their closed-source counterparts, particularly in GUI grounding and Out-Of-Distribution (OOD) scenarios. To facilitate future research in this area, we developed OS-Atlas - a foundational GUI action model that excels at GUI grounding and OOD agentic tasks through innovations in both data and modeling. We have invested significant engineering effort in developing an open-source toolkit for synthesizing GUI grounding data across multiple platforms, including Windows, Linux, MacOS, Android, and the web. Leveraging this toolkit, we are releasing the largest open-source cross-platform GUI grounding corpus to date, which contains over 13 million GUI elements. This dataset, combined with innovations in model training, provides a solid foundation for OS-Atlas to understand GUI screenshots and generalize to unseen interfaces. Through extensive evaluation across six benchmarks spanning three different platforms (mobile, desktop, and web), OS-Atlas demonstrates significant performance improvements over previous state-of-the-art models. Our evaluation also uncovers valuable insights into continuously improving and scaling the agentic capabilities of open-source VLMs.
Key facts. Cited by 370 papers in the map (data through 7 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 35 of its 42 references that are in the map. First posted on arXiv 30 Oct 2024.
Builds on
35 of 42 references.
Closest ancestors · 5
Same direction, newest first
- 2024Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents7 Oct
- 2024OmniParser for Pure Vision Based GUI Agent1 Aug
- 2024GUICourse: From General Vision Language Models to Versatile GUI Agents17 Jun
- 2024Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs8 Apr
- 2023CogAgent: A Visual Language Model for GUI Agents14 Dec
Other references · 30
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- 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,134
- 2024How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suitescited by 1,033
- 2024SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agentscited by 553
- 2024GPT-4V(ision) is a Generalist Web Agent, if Groundedcited by 547
- 2023Cognitive Architectures for Language Agentscited by 422
- 2022Pix2Struct: Screenshot Parsing as Pretraining for Visual Language Understandingcited by 360
- 2023AgentTuning: Enabling Generalized Agent Abilities for LLMscited by 319
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- 2024On the Effects of Data Scale on UI Control Agentscited by 187
- 2020Mapping Natural Language Instructions to Mobile UI Action Sequencescited by 180
- 2024Agent AI: Surveying the Horizons of Multimodal Interactioncited by 167
- 2024OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Webcited by 156
- 2024Android in the Zoo: Chain-of-Action-Thought for GUI Agentscited by 156
- 2024UFO: A UI-Focused Agent for Windows OS Interactioncited by 147
- 2021Screen2Words: Automatic Mobile UI Summarization with Multimodal Learningcited by 119
- 2024AMEX: Android Multi-annotation Expo Dataset for Mobile GUI Agentscited by 110
- 2024xLAM: A Family of Large Action Models to Empower AI Agent Systemscited by 108
- 2024Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Modelscited by 97
- 2021AndroidEnv: A Reinforcement Learning Platform for Androidcited by 90
- 2023Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaborationcited by 70
- 2024AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learningcited by 53
- 2024AgentStudio: A Toolkit for Building General Virtual Agentscited by 45
- 2020ActionBert: Leveraging User Actions for Semantic Understanding of User Interfacescited by 43
- 2024Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Modelscited by 13
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Citing papers per year: 2024: 7; 2025: 189; 2026: 174.
370 papers.
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