Instruction Agent: Enhancing Agent with Expert Demonstration
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Abstract (arXiv)
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 that leverages expert demonstrations to solve such tasks, enabling completion of otherwise difficult workflows. Given a single demonstration, the agent extracts step-by-step instructions and executes them by strictly following the trajectory intended by the user, which avoids making mistakes during execution. The agent leverages the verifier and backtracker modules further to improve robustness. Both modules are critical to understand the current outcome from each action and handle unexpected interruptions(such as pop-up windows) during execution. Our experiments show that Instruction Agent achieves a 60% success rate on a set of tasks in OSWorld that all top-ranked agents failed to complete. The Instruction Agent offers a practical and extensible framework, bridging the gap between current GUI agents and reliable real-world GUI task automation.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 28 references that are in the map. First posted on arXiv 8 Sep 2025.
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16 of 28 references.
References · 16
- 2024SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agentscited by 553
- 2024Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agentscited by 373
- 2024OS-ATLAS: A Foundation Action Model for Generalist GUI Agentscited by 370
- 2024On the Effects of Data Scale on UI Control Agentscited by 187
- 2025Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agentscited by 156
- 2024OS-Genesis: Automating GUI Agent Trajectory Construction via Reverse Task Synthesiscited by 155
- 2024UFO: A UI-Focused Agent for Windows OS Interactioncited by 147
- 2024AgentTrek: Agent Trajectory Synthesis via Guiding Replay with Web Tutorialscited by 123
- 2024GUI Agents with Foundation Models: A Comprehensive Surveycited by 110
- 2024NNetNav: Unsupervised Learning of Browser Agents Through Environment Interaction in the Wildcited by 55
- 2024VideoWebArena: Evaluating Long Context Multimodal Agents with Video Understanding Web Taskscited by 43
- 2025Magentic-UI: Towards Human-in-the-loop Agentic Systemscited by 41
4 more
- 2025CowPilot: A Framework for Autonomous and Human-Agent Collaborative Web Navigationcited by 35
- 2024LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrationscited by 32
- 2025Efficient Agent Training for Computer Usecited by 17
- 2025WinClick: GUI Grounding with Multimodal Large Language Modelscited by 11
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- 2026UI-Mate: Advancing Open-Weight Foundation GUI Agents with In-Context Demonstrations
- 2025BacktrackAgent: Enhancing GUI Agent with Error Detection and Backtracking Mechanism
- 2026DocOS: Towards Proactive Document-Guided Actions in GUI Agents
- 2026Do GUI Agents Know When Not to Act? Enabling Conflict-Aware Termination for Multimodal GUI Agents
- 2023ASSISTGUI: Task-Oriented Desktop Graphical User Interface Automation
- 2025PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC
- 2024Agent S: An Open Agentic Framework that Uses Computers Like a Human
- 2024GUI Agents: A Survey