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 324, 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 791, in read_json
json_reader = JsonReader(
path_or_buf,
...<16 lines>...
engine=engine,
)
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 905, in __init__
self.data = self._preprocess_data(data)
~~~~~~~~~~~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 917, in _preprocess_data
data = data.read()
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 844, in read_with_retries
out = read(*args, **kwargs)
File "<frozen codecs>", line 325, in decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x93 in position 0: invalid start byte
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 327, in _generate_tables
raise e
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, 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.
Layer 16: separate classifiers within each dataset
Open in Colab. Select L4/A100 → Run all. Downloads are anonymous; no Drive mount is needed.
Each task trains its own linear classifier on frozen layer-16 features, with training-only scaling and grouped cross-validation. Held-out scenes test whether a shared readout works within that dataset. Failure does not establish that the layer lacks the information. Classifier weights never transfer between datasets.
| Task | Labels | Groups kept together |
|---|---|---|
| MAT order | Intact / shuffled, including reversals | Four source variants |
| UCF order | Intact / shuffled, including reversals | 100 source groups |
| UCF direction | Forward / reverse intact videos | The same 100 groups |
| IntPhys continuity | Possible / impossible | 60 matched scenes |
The notebook has 7 code cells, 169 code lines and 241 words of explanation. Pixel change is the order/continuity baseline; endpoint pixels are the direction baseline. IntPhys probing is exploratory and differs from its standard benchmark protocol. MAT sources are closely related; human coherence ratings remain unmeasured.
Verified on 2026-09-29: all seven code cells completed on an NVIDIA L4 in 15 min 43 s, encoding all 1,296 inputs. Layer-16 held-out balanced accuracy: MAT order 100%, UCF order 94.6%, UCF direction 55.5%, IntPhys continuity 58.8%. These estimates alone do not establish statistical significance. Pixel change ranked intact above shuffled videos perfectly within sources, so order classification remains compatible with simple visual cues.
Files
temporal_coherence_colab.ipynb: complete raw-input workflow.temporal_coherence_colab_executed.ipynb: the same notebook with verified outputs.within_dataset_results.csv: current probe results;verification.jsonrecords checks and hashes.ucf_sources.json: fixed source selection and frame indices.mat_raw_frames.zip: lossless original pixels and frame orders; the defective two-frame condition is excluded during analysis.archive/supervised_study/: the previous study and its separate execution record.
The notebook pins the model, UCF and IntPhys2 revisions and downloads their assets directly. Their original terms apply. The supplied MAT stimuli have no asserted redistribution license.
Results, features and held-out predictions are saved to /content/layer16_within_dataset_results.zip.
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