The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ArrowInvalid
Message: JSON parse error: Invalid value. in row 0
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 342, in _generate_tables
df = pandas_read_json(f)
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
return pd.read_json(path_or_buf, **kwargs)
~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 815, in read_json
return json_reader.read()
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1014, in read
obj = self._get_object_parser(self.data)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1040, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1176, in parse
self._parse()
~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 1392, in _parse
ujson_loads(json, precise_float=self.precise_float), dtype=None
~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
During handling of the above exception, another exception occurred:
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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 345, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 291, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
DVIDIA | PiPER retention v0.2
A bounded native CPU study compares measured-joint, issued-joint and Cartesian hold strategies on twelve fresh synthetic scenes (36 attempts). The primary outcome is a continuous five-second hold after admission, checked against false confirmation. Every scheduled attempt and failure is retained. See report.json and the protocol for the frozen results and definitions.
This is not a learned policy, full transport or placement task, physical-sensor validation, hardware qualification or real-object reliability estimate. The simulator uses authored privileged state.
The ZIP preserves the complete new run tree under study/ and its independent audit under audit/. It includes deterministic inventory hashes and tools/verify_archive.py. To verify and optionally reconstruct without importing project code, extract the archive and run:
python tools/verify_archive.py piper-retention-v02.zip --output evidence
Research article: https://research.dvidia.org/papers/piper-retention-v02/ Source release: https://github.com/Dvidia-Inference/dvidia-training/releases/tag/piper-retention-v0.2-preview Evidence dataset: https://huggingface.co/datasets/Dvidia/piper-retention-v02
DVIDIA source and authored synthetic records are MIT. Upstream simulator and robot asset notices are included. No physical robot footage, credentials or hardware data are bundled.
Frozen results
| Hold | Admissions | False initial | Native 5 s grip | Grip + TCP stationarity | Final controller + native |
|---|---|---|---|---|---|
| measured_joint | 4/12 | 0 | 2/12 | 2/12 | 0/12 |
| issued_joint | 4/12 | 0 | 4/12 | 0/12 | 4/12 |
| cartesian | 4/12 | 0 | 4/12 | 0/12 | 0/12 |
Fresh finite development cells, not a population accuracy estimate. The separate development-smoke directory preserves the earlier selected old-case Cartesian refusal; it is excluded from all 36-attempt counts.
Archive SHA-256: 832cbf5ed26ad8a16fe873df0a2ea9c0a23818f95ed433025b8cb53b9613e99d
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