LearnAct
Collection
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Dataset Viewer
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Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 134, in _split_generators
analyze(archives, downloaded_dirs, split_name)
~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 108, in analyze
for downloaded_dir_file in dl_manager.iter_files(downloaded_dir):
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1430, in _iter_from_urlpaths
if xisfile(urlpath, download_config=download_config):
~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 745, in xisfile
fs, *_ = url_to_fs(path, **storage_options)
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/core.py", line 408, in url_to_fs
fs = filesystem(protocol, **inkwargs)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 303, in filesystem
return cls(**storage_options)
File "/usr/local/lib/python3.14/site-packages/fsspec/spec.py", line 81, in __call__
obj = super().__call__(*args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/fsspec/implementations/zip.py", line 62, in __init__
self.zip = zipfile.ZipFile(
~~~~~~~~~~~~~~~^
self.fo,
^^^^^^^^
...<3 lines>...
compresslevel=compresslevel,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/zipfile/__init__.py", line 1472, in __init__
self._RealGetContents()
~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/zipfile/__init__.py", line 1535, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.14/zipfile/__init__.py", line 375, in _EndRecData
return _EndRecData64(fpin, filesize - sizeEndCentDir, endrec)
File "/usr/local/lib/python3.14/zipfile/__init__.py", line 303, in _EndRecData64
raise BadZipFile("zipfiles that span multiple disks are not supported")
zipfile.BadZipFile: zipfiles that span multiple disks are not supported
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
LearnGUI: A Unified Demonstration Benchmark for Mobile GUI Agents
📄 Paper | 💻 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
📊 Dataset Structure and Statistics
The dataset is organized into three main splits:
Dataset Statistics
| Split | K-shot | Tasks | Apps | Step actions | Avg InsSim | Avg UISim | Avg ActSim | UISHActSH | UISHActSL | UISLActSH | UISLActSL |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Offline-Train | 1-shot | 2,001 | 44 | 26,184 | 0.845 | 0.901 | 0.858 | 364 | 400 | 403 | 834 |
| Offline-Train | 2-shot | 2,001 | 44 | 26,184 | 0.818 | 0.898 | 0.845 | 216 | 360 | 358 | 1,067 |
| Offline-Train | 3-shot | 2,001 | 44 | 26,184 | 0.798 | 0.895 | 0.836 | 152 | 346 | 310 | 1,193 |
| Offline-Test | 1-shot | 251 | 9 | 3,469 | 0.798 | 0.868 | 0.867 | 37 | 49 | 56 | 109 |
| Offline-Test | 2-shot | 251 | 9 | 3,469 | 0.767 | 0.855 | 0.853 | 15 | 42 | 55 | 139 |
| Offline-Test | 3-shot | 251 | 9 | 3,469 | 0.745 | 0.847 | 0.847 | 10 | 36 | 49 | 156 |
| Online-Test | 1-shot | 101 | 20 | 1,423 | - | - | - | - | - | - | - |
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
📁 Directory Structure
LearnGUI/
├── offline/ # Offline evaluation dataset
│ ├── screenshot.zip # Screenshot archives (multi-part)
│ ├── screenshot.z01-z05 # Screenshot archive parts
│ ├── element_anno.zip # Element annotations
│ ├── instruction_anno.zip # Instruction annotations
│ ├── task_spilit.json # Task splitting information
│ └── low_level_instructions.json # Detailed step-by-step instructions
│
└── online/ # Online evaluation dataset
├── low_level_instructions/ # JSON files with step instructions for each task
│ ├── AudioRecorderRecordAudio.json
│ ├── BrowserDraw.json
│ ├── SimpleCalendarAddOneEvent.json
│ └── ... (98 more task instruction files)
└── raw_data/ # Raw data for each online task
├── AudioRecorderRecordAudio/
├── BrowserDraw/
├── SimpleCalendarAddOneEvent/
└── ... (98 more task data directories)
Comparison with Existing Datasets
LearnGUI offers several advantages over existing GUI datasets:
| Dataset | # Inst. | # Apps | # Step | Env. | HL | LL | GT | FS |
|---|---|---|---|---|---|---|---|---|
| PixelHelp | 187 | 4 | 4.2 | ✗ | ✓ | ✗ | ✓ | ✗ |
| MoTIF | 276 | 125 | 4.5 | ✗ | ✓ | ✓ | ✓ | ✗ |
| UIBert | 16,660 | - | 1 | ✗ | ✗ | ✓ | ✓ | ✗ |
| UGIF | 523 | 12 | 6.3 | ✗ | ✓ | ✓ | ✓ | ✗ |
| AITW | 30,378 | 357 | 6.5 | ✗ | ✓ | ✗ | ✓ | ✗ |
| AITZ | 2,504 | 70 | 7.5 | ✗ | ✓ | ✓ | ✓ | ✗ |
| AndroidControl | 15,283 | 833 | 4.8 | ✗ | ✓ | ✓ | ✓ | ✗ |
| AMEX | 2,946 | 110 | 12.8 | ✗ | ✓ | ✗ | ✓ | ✗ |
| MobileAgentBench | 100 | 10 | - | ✗ | ✓ | ✗ | ✗ | ✗ |
| AppAgent | 50 | 10 | - | ✗ | ✓ | ✗ | ✗ | ✗ |
| LlamaTouch | 496 | 57 | 7.01 | ✓ | ✓ | ✗ | ✓ | ✗ |
| AndroidWorld | 116 | 20 | - | ✓ | ✓ | ✗ | ✗ | ✗ |
| AndroidLab | 138 | 9 | 8.5 | ✓ | ✓ | ✗ | ✗ | ✗ |
| LearnGUI (Ours) | 2,353 | 73 | 13.2 | ✓ | ✓ | ✓ | ✓ | ✓ |
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).
📄 License
This dataset is licensed under Apache License 2.0.
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