Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
task_id: string
instruction: string
criteria: list<item: struct<id: string, description: string>>
child 0, item: struct<id: string, description: string>
child 0, id: string
child 1, description: string
type: string
difficulty_level: string
source: string
resources: struct<input_file: string>
child 0, input_file: string
id: string
reference_output: struct<expected_file: string>
child 0, expected_file: string
rubric_file: string
layer_related: bool
to
{'id': Value('string'), 'instruction': Value('string'), 'difficulty_level': Value('string'), 'type': Value('string'), 'resources': {'input_file': Value('string')}, 'reference_output': {'expected_file': Value('string')}, 'source': Value('string'), 'layer_related': Value('bool'), 'rubric_file': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
task_id: string
instruction: string
criteria: list<item: struct<id: string, description: string>>
child 0, item: struct<id: string, description: string>
child 0, id: string
child 1, description: string
type: string
difficulty_level: string
source: string
resources: struct<input_file: string>
child 0, input_file: string
id: string
reference_output: struct<expected_file: string>
child 0, expected_file: string
rubric_file: string
layer_related: bool
to
{'id': Value('string'), 'instruction': Value('string'), 'difficulty_level': Value('string'), 'type': Value('string'), 'resources': {'input_file': Value('string')}, 'reference_output': {'expected_file': Value('string')}, 'source': Value('string'), 'layer_related': Value('bool'), 'rubric_file': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PSBench
PSBench is a benchmark for evaluating GUI agents on 600 image-editing tasks in Adobe Photoshop. The accompanying paper, “PSBench: Editing Image via GUI Agents in Photoshop,” has been accepted to ICML 2026.
For evaluation stability and reproducibility, PSBench uses task-specific, rubric-based LLM-as-a-judge evaluation. The runtime judge compares the original START image with the candidate RESULT image and evaluates only the visible requirements in the task rubric. The author-created END image is not provided to the runtime judge.
The benchmark source code and setup instructions are available in the PSBench GitHub repository.
Dataset Structure
The dataset contains 600 directories named 001 through 600. Each directory contains four core task files:
<id>.json: the English task instruction and task metadata.<id>_rubric.json: task-specific visible-result evaluation criteria.- START image: the source image supplied to the GUI agent. Its filename is declared by
resources.input_filein the task JSON. - END image: an author-created successful result used to develop and validate the rubric. Its filename is declared by
reference_output.expected_filein the task JSON.
Tasks derived from YouTube tutorials additionally include their original tutorial video. The published dataset contains 190 MP4 files. Photoshop project files used during task development are not included.
001/
|-- 001.json
|-- 001_rubric.json
|-- 001_start.jpg
`-- 001_end.jpg
Image filenames and extensions are configuration-driven and may differ from the example above.
Download
Install the Hugging Face command-line client:
pip install -U huggingface_hub
From the root of a PSBench source-code checkout, download the task package into tasks/:
hf download zyn1216/PSBench --repo-type dataset --local-dir tasks --exclude "README.md" ".gitattributes"
The resulting layout should contain tasks/001 through tasks/600.
Adobe Photoshop Requirement
Adobe Photoshop is commercial software and is not distributed with this dataset. Users must purchase or otherwise obtain a valid Photoshop license and install the application separately. Photoshop 2024 on Windows is recommended for reproducibility.
License
PSBench is released under the MIT License.
Citation
@inproceedings{
zhang2026psbench,
title={{PSB}ench: Editing Image via {GUI} Agents in Photoshop},
author={Yinuo Zhang and Zian Cheng and Ziya Zhao and Zongyu Li and Bingshuo Liu and Qingbin Liu and Junxian Cai and Xi Chen and Zhiying Tu and Dianhui Chu and Xiaoyan Yu and Dianbo Sui},
booktitle={Forty-third International Conference on Machine Learning},
year={2026},
url={https://openreview.net/forum?id=O93cZGxYB1}
}
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