Prompt2Task: Automating UI Tasks on Smartphones from Textual Prompts
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Abstract (arXiv)
UI task automation enables efficient task execution by simulating human interactions with graphical user interfaces (GUIs), without modifying the existing application code. However, its broader adoption is constrained by the need for expertise in both scripting languages and workflow design. To address this challenge, we present Prompt2Task, a system designed to comprehend various task-related textual prompts (e.g., goals, procedures), thereby generating and performing the corresponding automation tasks. Prompt2Task incorporates a suite of intelligent agents that mimic human cognitive functions, specializing in interpreting user intent, managing external information for task generation, and executing operations on smartphones. The agents can learn from user feedback and continuously improve their performance based on the accumulated knowledge. Experimental results indicated a performance jump from a 22.28% success rate in the baseline to 95.24% with Prompt2Task, requiring an average of 0.69 user interventions for each new task. Prompt2Task presents promising applications in fields such as tutorial creation, smart assistance, and customer service.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Apr 2024.
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Citing papers per year: 2024: 3; 2025: 4; 2026: 1.
8 papers.
- 2024Large Language Model-Brained GUI Agents: A Surveycited by 160
- 2024WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Modelscited by 28
- 2025Characterizing Unintended Consequences in Human-GUI Agent Collaboration for Web Browsingcited by 7
- 2025EcoAgent: An Efficient Device-Cloud Collaborative Multi-Agent Framework for Mobile Automationcited by 6
- 2025UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spacescited by 4
- 2025DuetUI: A Bidirectional Context Loop for Human-Agent Co-Generation of Task-Oriented Interfacescited by 3
- 2024Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Taskscited by 2
- 2026Software Engineering for and with GUI Agentcited by 1
- 2026Software Engineering for and with GUI Agent10 Aug 2026
- 2025DuetUI: A Bidirectional Context Loop for Human-Agent Co-Generation of Task-Oriented Interfaces16 Sep 2025
- 2025Characterizing Unintended Consequences in Human-GUI Agent Collaboration for Web Browsing15 May 2025
- 2025EcoAgent: An Efficient Device-Cloud Collaborative Multi-Agent Framework for Mobile Automation8 May 2025
- 2025UserCentrix: An Agentic Memory-augmented AI Framework for Smart Spaces1 May 2025
- 2024Large Language Model-Brained GUI Agents: A Survey27 Nov 2024
- 2024WorkflowLLM: Enhancing Workflow Orchestration Capability of Large Language Models8 Nov 2024
- 2024Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Tasks4 Oct 2024