The dataset viewer is not available for this subset.
Exception: HfHubHTTPError
Message: (Request ID: Root=1-6a6733d7-0cd1041e3dc89c1654ad9914;c131e87b-a0a1-40dc-a11b-0a028c3f2b0a)
429 Too Many Requests: you have reached your 'api' rate limit.
Retry after 157 seconds (0/500 requests remaining in current 300s window).
Url: https://huggingface.co/api/datasets/zhouyiqun/TUTOR-Bench/revision/90db1432d69a227a27f2bbefdf7f7326f98efe90.
We had to rate limit your IP (44.222.55.104). To continue using our service, create a HF account or login to your existing account, and make sure you pass a HF_TOKEN if you're using the API.
Traceback: 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 268, in get_dataset_config_info
builder = load_dataset_builder(
path,
...<6 lines>...
**config_kwargs,
)
File "/src/services/worker/src/worker/utils.py", line 390, in safe_load_dataset_builder
dataset_module = dataset_module_factory(
repo_dir,
revision=revision,
download_config=download_config,
)
File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1217, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1192, in dataset_module_factory
).get_module()
~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 608, in get_module
standalone_yaml_path = cached_path(
hf_dataset_url(self.name, config.REPOYAML_FILENAME, revision=self.commit_hash),
download_config=download_config,
)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 180, in cached_path
).resolve_path(url_or_filename)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 339, in resolve_path
repo_and_revision_exist, err = self._repo_and_revision_exist(parsed.type, parsed.id, revision)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 252, in _repo_and_revision_exist
self._api.repo_info(
~~~~~~~~~~~~~~~~~~~^
repo_id, revision=revision, repo_type=repo_type, timeout=constants.HF_HUB_ETAG_TIMEOUT
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
return fn(*args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_api.py", line 3598, in repo_info
return method(
repo_id,
...<4 lines>...
files_metadata=files_metadata,
)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_validators.py", line 88, in _inner_fn
return fn(*args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_api.py", line 3360, in dataset_info
hf_raise_for_status(r)
~~~~~~~~~~~~~~~~~~~^^^
File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 868, in hf_raise_for_status
raise _format(HfHubHTTPError, message, response) from e
huggingface_hub.errors.HfHubHTTPError: (Request ID: Root=1-6a6733d7-0cd1041e3dc89c1654ad9914;c131e87b-a0a1-40dc-a11b-0a028c3f2b0a)
429 Too Many Requests: you have reached your 'api' rate limit.
Retry after 157 seconds (0/500 requests remaining in current 300s window).
Url: https://huggingface.co/api/datasets/zhouyiqun/TUTOR-Bench/revision/90db1432d69a227a27f2bbefdf7f7326f98efe90.
We had to rate limit your IP (44.222.55.104). To continue using our service, create a HF account or login to your existing account, and make sure you pass a HF_TOKEN if you're using the API.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.
TUTOR-Bench
TUTOR-Bench measures directed cross-task demonstration utility under a fixed robot-learning intervention. For a target task (i) and donor task (j), utility is the paired closed-loop success-rate change between a 9:1 target--donor training condition and matched target-only training.
The primary release contains 14 selected LIBERO tasks, 182 ordered non-self cells, 588 training runs, and 5,880 utility-panel rollouts. Every policy uses 10 fixed utility scenarios and every matrix cell aggregates three training seeds. It also contains the target-only provenance used to select the 14-task roster from 40 candidates using an inclusive pooled-success threshold of 0.20.
Data Files
data/tasks.jsonl: 40 candidate tasks, calibration operating points, eligibility outcomes, and the 14-task membership flag.data/episodes.jsonl: 800 stable source episode references; raw demonstrations are not included.data/training_runs.jsonl: 546 mixed and 42 reused target-only runs.data/rollouts.jsonl.gz: 5,460 mixed and 420 target-only outcomes.data/utilities.jsonlanddata/utility_matrix.tsv: 182 complete aggregate utility cells.benchmark/primary/: frozen splits, features, predictions, and scores.benchmark/completion/: full compressed trial tables and summary records.
The source demonstrations are identified by the pinned
HuggingFaceVLA/libero revision recorded in MANIFEST.json. This dataset does
not contain LIBERO demonstration bytes, simulator assets, videos, action traces,
or checkpoints.
Intended Use
The dataset supports donor selection, signed utility regression, ranking, and budgeted within-row utility completion under the released protocol. It does not measure learner-independent task similarity and should not be used to infer utility for excluded tasks, unseen donors, other mixing ratios, other learners, or real-world embodiments without new closed-loop evidence.
Full definitions, missingness rules, and reconstruction commands are provided in the companion GitHub repository and the release manifest.
License
Project-generated data and benchmark artifacts are licensed under Creative
Commons Attribution 4.0 International (CC-BY-4.0); see DATA_LICENSE for the
grant and attribution requirements. The source demonstrations, LIBERO assets,
model weights, and other third-party material are not relicensed and are not
included. Stable upstream references remain subject to their original terms as
described in the companion repository's THIRD_PARTY.md and upstream notices.
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