The dataset viewer is not available for this subset.
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/webdataset/webdataset.py", line 81, in _split_generators
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
~~~~~~~~~~~~~~~~~^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
cls = get_filesystem_class(protocol)
File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
raise ValueError(f"Protocol not known: {protocol}")
ValueError: Protocol not known: memory
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.
TriWorldBench Dataset
Welcome to TriWorldBench, a benchmark for evaluating triple-view embodied world models.
- Benchmark homepage: https://www.triworldbench.com
- Benchmark code repository: TriWorldBench/TriWorldBench
Overview
TriWorldBench evaluates world models from three synchronized robot views: head, left wrist, and right wrist. The benchmark focuses on whether a model can generate one coherent robot world across all three cameras while preserving task alignment, physical and 3D coherence, motion quality, temporal consistency, and visual quality.
Released Files
This Hugging Face dataset provides two compressed dataset bundles:
test_dataset: the official 500-episode test set for leaderboard submission.val_dataset: a 100-episode validation bundle for local development and quick evaluation.
test_dataset Structure
After extraction, the official test dataset is organized as:
test_dataset/
+-- data/
| +-- episode1.hdf5
| +-- episode2.hdf5
| +-- ...
| +-- episode500.hdf5
+-- first_frame/
| +-- episode1_head.jpg
| +-- episode1_left.jpg
| +-- episode1_right.jpg
| +-- ...
| +-- episode500_right.jpg
+-- instructions/
+-- episode1.json
+-- episode2.json
+-- ...
+-- episode500.json
The test set contains 500 episodes indexed from episode1 to episode500.
For each episode, data/episodeN.hdf5 contains the trajectory/action sequence,
first_frame/ provides the initial 320x240 observations for the head, left wrist,
and right wrist cameras, and instructions/episodeN.json contains the task instruction.
Participants should run their models on this test set and submit generated videos
for all three views: head.mp4, left.mp4, and right.mp4.
val_dataset Structure
The validation bundle contains 100 episodes derived from RoboTwin2.0, together with the corresponding ground-truth data and processed state annotations. After extraction, it is organized as:
val_dataset/
+-- test_dataset/
| +-- data/
| +-- first_frame/
| +-- instructions/
+-- STATE/
| +-- episode*.json
+-- gt_dataset/
+-- episode*/
The val_dataset/test_dataset folder provides the same type of model inputs as
the official test set. The bundled gt_dataset and STATE folders are already
formatted for the TriWorldBench evaluation code. Matching VQA question annotations
for this validation set are included in the benchmark code repository under
metrics/VQA/qa_val/.
Evaluation and Submission
Please refer to the benchmark homepage and code repository for environment setup, inference, evaluation, and leaderboard submission instructions.
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