AgentStudio: A Toolkit for Building General Virtual Agents
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Cited by 24 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
General virtual agents need to handle multimodal observations, master complex action spaces, and self-improve in dynamic, open-domain environments. However, existing environments are often domain-specific and require complex setups, which limits agent development and evaluation in real-world settings. As a result, current evaluations lack in-depth analyses that decompose fundamental agent capabilities. We introduce AgentStudio, a trinity of environments, tools, and benchmarks to address these issues. AgentStudio provides a lightweight, interactive environment with highly generic observation and action spaces, e.g., video observations and GUI/API actions. It integrates tools for creating online benchmark tasks, annotating GUI elements, and labeling actions in videos. Based on our environment and tools, we curate an online task suite that benchmarks both GUI interactions and function calling with efficient auto-evaluation. We also reorganize existing datasets and collect new ones using our tools to establish three datasets: GroundUI, IDMBench, and CriticBench. These datasets evaluate fundamental agent abilities, including GUI grounding, learning from videos, and success detection, pointing to the desiderata for robust, general, and open-ended virtual agents.
Key facts. Cited by 45 papers in the map (data through 14 Oct 2026). Builds on 42 of its 53 references that are in the map. First posted on arXiv 26 Mar 2024.
Builds on
42 of 53 references.
References · 42
- 2020Language Models are Few-Shot Learnerscited by 32,419
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- 2022WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agentscited by 1,251
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- 2023Android in the Wild: A Large-Scale Dataset for Android Device Controlcited by 319
- 2018Reinforcement Learning on Web Interfaces Using Workflow-Guided Explorationcited by 284
- 2024OS-Copilot: Towards Generalist Computer Agents with Self-Improvementcited by 205
- 2023Synapse: Trajectory-as-Exemplar Prompting with Memory for Computer Controlcited by 187
- 2020Mapping Natural Language Instructions to Mobile UI Action Sequencescited by 181
- 2024WebLINX: Real-World Website Navigation with Multi-Turn Dialoguecited by 180
- 2024OmniACT: A Dataset and Benchmark for Enabling Multimodal Generalist Autonomous Agents for Desktop and Webcited by 157
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- 2023OpenAgents: An Open Platform for Language Agents in the Wildcited by 137
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- 2024ScreenAgent: A Vision Language Model-driven Computer Control Agentcited by 102
- 2021AndroidEnv: A Reinforcement Learning Platform for Androidcited by 90
- 2022A data-driven approach for learning to control computerscited by 88
- 2024Scaling Instructable Agents Across Many Simulated Worldscited by 71
- 2023Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Modelscited by 68
- 2022A Dataset for Interactive Vision-Language Navigation with Unknown Command Feasibilitycited by 61
- 2018Learning to Navigate the Webcited by 60
- 2023SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Modelscited by 57
- 2022Environment Generation for Zero-Shot Compositional Reinforcement Learningcited by 32
- 2023PPTC Benchmark: Evaluating Large Language Models for PowerPoint Task Completioncited by 30
- 2019DOM-Q-NET: Grounded RL on Structured Languagecited by 25
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Citing papers per year: 2024: 10; 2025: 25; 2026: 10.
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- 2026UI-Voyager: A Self-Evolving GUI Agent Learning via Failed Experience25 Mar 2026
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- 2026HATS: Hardness-Aware Trajectory Synthesis for GUI Agentscited by 9
- 2025Guiding VLM Agents with Process Rewards at Inference Time for GUI Navigationcited by 8
- 2025Empowering Multimodal LLMs with External Tools: A Comprehensive Surveycited by 2
- 2025Leveraging Vision-Language Models for Visual Grounding and Analysis of Automotive UIcited by 1
- 2026HATS: Hardness-Aware Trajectory Synthesis for GUI Agents12 Mar 2026
- 2025FineVision: Open Data Is All You Need20 Oct 2025
- 2025Empowering Multimodal LLMs with External Tools: A Comprehensive Survey14 Aug 2025
- 2025OpenCUA: Open Foundations for Computer-Use Agents12 Aug 2025
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- 2025Guiding VLM Agents with Process Rewards at Inference Time for GUI Navigation22 Apr 2025
- 2025Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models20 Jan 2025
- 2024MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs22 Nov 2024
- 2024OS-ATLAS: A Foundation Action Model for Generalist GUI Agents30 Oct 2024
- 2024VipAct: Visual-Perception Enhancement via Specialized VLM Agent Collaboration and Tool-use21 Oct 2024
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- 2025Exploring the Link Between Bayesian Inference and Embodied Intelligence: Toward Open Physical-World Embodied AI Systems29 Jul 2025
- 2025Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries9 Jun 2025
- 2025The Amazon Nova Family of Models: Technical Report and Model Card17 Mar 2025
- 2025DeskVision: Large Scale Desktop Region Captioning for Advanced GUI Agents14 Mar 2025
- 2024Iris: Breaking GUI Complexity with Adaptive Focus and Self-Refining13 Dec 2024
- 2024Ferret-UI 2: Mastering Universal User Interface Understanding Across Platforms24 Oct 2024
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