lgy0404/LearnGUI

Dataset

LearnGUI: A Unified Demonstration Benchmark for Mobile GUI Agents

8

20 commits

2 linked in READMEs

updated May 6, 2025

See the code

README

LearnGUI: A Unified Demonstration Benchmark for Mobile GUI Agents

The LearnAct Framework and LearnGUI Benchmark focus on addressing the long-tail challenges in mobile GUI agent performance through demonstration-based learning.

πŸ“„ Paper | πŸ’» Code | 🌐 Project Page

Overview

LearnGUI is the first comprehensive dataset specifically designed for studying demonstration-based learning in mobile GUI agents. It comprises 2,353 instructions across 73 applications with an average of 13.2 steps per task, featuring high-quality human demonstrations for both offline and online evaluation scenarios.

🌟 Key Features

  • Unified Benchmark Framework: Provides standardized metrics and evaluation protocols for demonstration-based learning in mobile GUI agents
  • Dual Evaluation Modes: Supports both offline (2,252 tasks) and online (101 tasks) evaluation scenarios to assess agent performance
  • Rich Few-shot Learning Support: Includes k-shot combinations (k=1,2,3) for each task with varying similarity profiles
  • Multi-dimensional Similarity Metrics: Quantifies demonstration relevance across instruction, UI, and action dimensions
  • Diverse Real-world Coverage: Spans 73 mobile applications with 2,353 naturally varied tasks reflecting real-world usage patterns
  • Expert-annotated Trajectories: Contains high-quality human demonstrations with detailed step-by-step action sequences and element annotations

πŸ“Š Dataset Structure and Statistics

The dataset is organized into three main splits:

Dataset Statistics

SplitK-shotTasksAppsStep actionsAvg InsSimAvg UISimAvg ActSimUISHActSHUISHActSLUISLActSHUISLActSL
Offline-Train1-shot2,0014426,1840.8450.9010.858364400403834
Offline-Train2-shot2,0014426,1840.8180.8980.8452163603581,067
Offline-Train3-shot2,0014426,1840.7980.8950.8361523463101,193
Offline-Test1-shot25193,4690.7980.8680.867374956109
Offline-Test2-shot25193,4690.7670.8550.853154255139
Offline-Test3-shot25193,4690.7450.8470.847103649156
Online-Test1-shot101201,423-------

Each task in LearnGUI contains:

  • High-level instruction
  • Low-level action sequences
  • Screenshot of each step
  • UI element details
  • Ground truth action labels
  • Demonstration pairings with varying similarity profiles

πŸ“ Directory Structure

LearnGUI/
β”œβ”€β”€ offline/                            # Offline evaluation dataset
β”‚   β”œβ”€β”€ screenshot.zip                  # Screenshot archives (multi-part)
β”‚   β”œβ”€β”€ screenshot.z01-z05              # Screenshot archive parts
β”‚   β”œβ”€β”€ element_anno.zip                # Element annotations
β”‚   β”œβ”€β”€ instruction_anno.zip            # Instruction annotations
β”‚   β”œβ”€β”€ task_spilit.json                # Task splitting information
β”‚   └── low_level_instructions.json     # Detailed step-by-step instructions
β”‚
└── online/                             # Online evaluation dataset
    β”œβ”€β”€ low_level_instructions/         # JSON files with step instructions for each task
    β”‚   β”œβ”€β”€ AudioRecorderRecordAudio.json
    β”‚   β”œβ”€β”€ BrowserDraw.json
    β”‚   β”œβ”€β”€ SimpleCalendarAddOneEvent.json
    β”‚   └── ... (98 more task instruction files)
    └── raw_data/                       # Raw data for each online task
        β”œβ”€β”€ AudioRecorderRecordAudio/
        β”œβ”€β”€ BrowserDraw/
        β”œβ”€β”€ SimpleCalendarAddOneEvent/
        └── ... (98 more task data directories)

Comparison with Existing Datasets

LearnGUI offers several advantages over existing GUI datasets:

Dataset# Inst.# Apps# StepEnv.HLLLGTFS
PixelHelp18744.2βœ—βœ“βœ—βœ“βœ—
MoTIF2761254.5βœ—βœ“βœ“βœ“βœ—
UIBert16,660-1βœ—βœ—βœ“βœ“βœ—
UGIF523126.3βœ—βœ“βœ“βœ“βœ—
AITW30,3783576.5βœ—βœ“βœ—βœ“βœ—
AITZ2,504707.5βœ—βœ“βœ“βœ“βœ—
AndroidControl15,2838334.8βœ—βœ“βœ“βœ“βœ—
AMEX2,94611012.8βœ—βœ“βœ—βœ“βœ—
MobileAgentBench10010-βœ—βœ“βœ—βœ—βœ—
AppAgent5010-βœ—βœ“βœ—βœ—βœ—
LlamaTouch496577.01βœ“βœ“βœ—βœ“βœ—
AndroidWorld11620-βœ“βœ“βœ—βœ—βœ—
AndroidLab13898.5βœ“βœ“βœ—βœ—βœ—
LearnGUI (Ours)2,3537313.2βœ“βœ“βœ“βœ“βœ“

Note: # Inst. (number of instructions), # Apps (number of applications), # Step (average steps per task), Env. (supports environment interactions), HL (has high-level instructions), LL (has low-level instructions), GT (provides ground truth trajectories), FS (supports few-shot learning).

πŸ“„ License

This dataset is licensed under Apache License 2.0.

Contributors

lgy0404

19 commits

nielsr

1 commits

lgy0404/LearnGUI

Dataset

LearnGUI: A Unified Demonstration Benchmark for Mobile GUI Agents

8

20 commits

2 linked in READMEs

updated May 6, 2025

See the code

README

LearnGUI: A Unified Demonstration Benchmark for Mobile GUI Agents

The LearnAct Framework and LearnGUI Benchmark focus on addressing the long-tail challenges in mobile GUI agent performance through demonstration-based learning.

πŸ“„ Paper | πŸ’» Code | 🌐 Project Page

Overview

LearnGUI is the first comprehensive dataset specifically designed for studying demonstration-based learning in mobile GUI agents. It comprises 2,353 instructions across 73 applications with an average of 13.2 steps per task, featuring high-quality human demonstrations for both offline and online evaluation scenarios.

🌟 Key Features

  • Unified Benchmark Framework: Provides standardized metrics and evaluation protocols for demonstration-based learning in mobile GUI agents
  • Dual Evaluation Modes: Supports both offline (2,252 tasks) and online (101 tasks) evaluation scenarios to assess agent performance
  • Rich Few-shot Learning Support: Includes k-shot combinations (k=1,2,3) for each task with varying similarity profiles
  • Multi-dimensional Similarity Metrics: Quantifies demonstration relevance across instruction, UI, and action dimensions
  • Diverse Real-world Coverage: Spans 73 mobile applications with 2,353 naturally varied tasks reflecting real-world usage patterns
  • Expert-annotated Trajectories: Contains high-quality human demonstrations with detailed step-by-step action sequences and element annotations

πŸ“Š Dataset Structure and Statistics

The dataset is organized into three main splits:

Dataset Statistics

SplitK-shotTasksAppsStep actionsAvg InsSimAvg UISimAvg ActSimUISHActSHUISHActSLUISLActSHUISLActSL
Offline-Train1-shot2,0014426,1840.8450.9010.858364400403834
Offline-Train2-shot2,0014426,1840.8180.8980.8452163603581,067
Offline-Train3-shot2,0014426,1840.7980.8950.8361523463101,193
Offline-Test1-shot25193,4690.7980.8680.867374956109
Offline-Test2-shot25193,4690.7670.8550.853154255139
Offline-Test3-shot25193,4690.7450.8470.847103649156
Online-Test1-shot101201,423-------

Each task in LearnGUI contains:

  • High-level instruction
  • Low-level action sequences
  • Screenshot of each step
  • UI element details
  • Ground truth action labels
  • Demonstration pairings with varying similarity profiles

πŸ“ Directory Structure

LearnGUI/
β”œβ”€β”€ offline/                            # Offline evaluation dataset
β”‚   β”œβ”€β”€ screenshot.zip                  # Screenshot archives (multi-part)
β”‚   β”œβ”€β”€ screenshot.z01-z05              # Screenshot archive parts
β”‚   β”œβ”€β”€ element_anno.zip                # Element annotations
β”‚   β”œβ”€β”€ instruction_anno.zip            # Instruction annotations
β”‚   β”œβ”€β”€ task_spilit.json                # Task splitting information
β”‚   └── low_level_instructions.json     # Detailed step-by-step instructions
β”‚
└── online/                             # Online evaluation dataset
    β”œβ”€β”€ low_level_instructions/         # JSON files with step instructions for each task
    β”‚   β”œβ”€β”€ AudioRecorderRecordAudio.json
    β”‚   β”œβ”€β”€ BrowserDraw.json
    β”‚   β”œβ”€β”€ SimpleCalendarAddOneEvent.json
    β”‚   └── ... (98 more task instruction files)
    └── raw_data/                       # Raw data for each online task
        β”œβ”€β”€ AudioRecorderRecordAudio/
        β”œβ”€β”€ BrowserDraw/
        β”œβ”€β”€ SimpleCalendarAddOneEvent/
        └── ... (98 more task data directories)

Comparison with Existing Datasets

LearnGUI offers several advantages over existing GUI datasets:

Dataset# Inst.# Apps# StepEnv.HLLLGTFS
PixelHelp18744.2βœ—βœ“βœ—βœ“βœ—
MoTIF2761254.5βœ—βœ“βœ“βœ“βœ—
UIBert16,660-1βœ—βœ—βœ“βœ“βœ—
UGIF523126.3βœ—βœ“βœ“βœ“βœ—
AITW30,3783576.5βœ—βœ“βœ—βœ“βœ—
AITZ2,504707.5βœ—βœ“βœ“βœ“βœ—
AndroidControl15,2838334.8βœ—βœ“βœ“βœ“βœ—
AMEX2,94611012.8βœ—βœ“βœ—βœ“βœ—
MobileAgentBench10010-βœ—βœ“βœ—βœ—βœ—
AppAgent5010-βœ—βœ“βœ—βœ—βœ—
LlamaTouch496577.01βœ“βœ“βœ—βœ“βœ—
AndroidWorld11620-βœ“βœ“βœ—βœ—βœ—
AndroidLab13898.5βœ“βœ“βœ—βœ—βœ—
LearnGUI (Ours)2,3537313.2βœ“βœ“βœ“βœ“βœ“

Note: # Inst. (number of instructions), # Apps (number of applications), # Step (average steps per task), Env. (supports environment interactions), HL (has high-level instructions), LL (has low-level instructions), GT (provides ground truth trajectories), FS (supports few-shot learning).

πŸ“„ License

This dataset is licensed under Apache License 2.0.

Contributors

lgy0404

19 commits

nielsr

1 commits