The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
as_of_date: timestamp[s]
builder: string
content_blockers: list<item: null>
child 0, item: null
git_independent: bool
integrity: struct<algorithm: string, index: string, index_excludes: list<item: string>, reason: string>
child 0, algorithm: string
child 1, index: string
child 2, index_excludes: list<item: string>
child 0, item: string
child 3, reason: string
license_choice: string
metadata_release_note: string
owner_blockers: list<item: null>
child 0, item: null
quality_gates: struct<content_audit: struct<finding_count: int64, status: string>, focused_snapshot_tests: struct<m (... 489 chars omitted)
child 0, content_audit: struct<finding_count: int64, status: string>
child 0, finding_count: int64
child 1, status: string
child 1, focused_snapshot_tests: struct<model_free: bool, returncode: int64, status: string, tests: list<item: string>>
child 0, model_free: bool
child 1, returncode: int64
child 2, status: string
child 3, tests: list<item: string>
child 0, item: string
child 2, generated_artifacts: struct<finding_count: int64, status: string>
child 0, finding_count: int64
child 1, status: string
child 3, generated_index_audit: struct<finding_count: int64, status: string>
child 0, finding_count: int64
child 1, status: string
child 4, manifest_completeness: struct<definition: string, finding_count: int64, status: string>
child 0, definition: string
child 1, finding_cou
...
omitted)
child 0, blocked_candidate_path_count: int64
child 1, blocker_count: int64
child 2, blockers_by_check: struct<absolute_machine_path: int64, content_scan_limit: int64, internal_domain: int64, large_file: (... 36 chars omitted)
child 0, absolute_machine_path: int64
child 1, content_scan_limit: int64
child 2, internal_domain: int64
child 3, large_file: int64
child 4, private_governance_id: int64
child 3, candidate_bytes: int64
child 4, candidate_file_count: int64
child 5, release_ready_bytes: int64
child 6, release_ready_file_count: int64
network_access: bool
metadata_only: bool
files: list<item: struct<mode: string, path: string, reason: string, sha256: string, size_bytes: int64, sou (... 13 chars omitted)
child 0, item: struct<mode: string, path: string, reason: string, sha256: string, size_bytes: int64, source: string (... 1 chars omitted)
child 0, mode: string
child 1, path: string
child 2, reason: string
child 3, sha256: string
child 4, size_bytes: int64
child 5, source: string
source_public_snapshot: struct<as_of_date: timestamp[s], checksum_index_sha256: string, manifest_sha256: string, payload_fil (... 69 chars omitted)
child 0, as_of_date: timestamp[s]
child 1, checksum_index_sha256: string
child 2, manifest_sha256: string
child 3, payload_file_count: int64
child 4, release_status: string
child 5, snapshot_content_ready: bool
upload_performed: bool
token_access: bool
to
{'builder': Value('string'), 'files': List({'mode': Value('string'), 'path': Value('string'), 'reason': Value('string'), 'sha256': Value('string'), 'size_bytes': Value('int64'), 'source': Value('string')}), 'integrity': {'algorithm': Value('string'), 'index': Value('string'), 'index_excludes': List(Value('string')), 'manifest_inventory_excludes': List(Value('string')), 'reason': Value('string')}, 'metadata_only': Value('bool'), 'network_access': Value('bool'), 'schema_version': Value('string'), 'source_public_snapshot': {'as_of_date': Value('timestamp[s]'), 'checksum_index_sha256': Value('string'), 'manifest_sha256': Value('string'), 'payload_file_count': Value('int64'), 'release_status': Value('string'), 'snapshot_content_ready': Value('bool')}, 'token_access': Value('bool'), 'upload_performed': Value('bool')}
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 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
as_of_date: timestamp[s]
builder: string
content_blockers: list<item: null>
child 0, item: null
git_independent: bool
integrity: struct<algorithm: string, index: string, index_excludes: list<item: string>, reason: string>
child 0, algorithm: string
child 1, index: string
child 2, index_excludes: list<item: string>
child 0, item: string
child 3, reason: string
license_choice: string
metadata_release_note: string
owner_blockers: list<item: null>
child 0, item: null
quality_gates: struct<content_audit: struct<finding_count: int64, status: string>, focused_snapshot_tests: struct<m (... 489 chars omitted)
child 0, content_audit: struct<finding_count: int64, status: string>
child 0, finding_count: int64
child 1, status: string
child 1, focused_snapshot_tests: struct<model_free: bool, returncode: int64, status: string, tests: list<item: string>>
child 0, model_free: bool
child 1, returncode: int64
child 2, status: string
child 3, tests: list<item: string>
child 0, item: string
child 2, generated_artifacts: struct<finding_count: int64, status: string>
child 0, finding_count: int64
child 1, status: string
child 3, generated_index_audit: struct<finding_count: int64, status: string>
child 0, finding_count: int64
child 1, status: string
child 4, manifest_completeness: struct<definition: string, finding_count: int64, status: string>
child 0, definition: string
child 1, finding_cou
...
omitted)
child 0, blocked_candidate_path_count: int64
child 1, blocker_count: int64
child 2, blockers_by_check: struct<absolute_machine_path: int64, content_scan_limit: int64, internal_domain: int64, large_file: (... 36 chars omitted)
child 0, absolute_machine_path: int64
child 1, content_scan_limit: int64
child 2, internal_domain: int64
child 3, large_file: int64
child 4, private_governance_id: int64
child 3, candidate_bytes: int64
child 4, candidate_file_count: int64
child 5, release_ready_bytes: int64
child 6, release_ready_file_count: int64
network_access: bool
metadata_only: bool
files: list<item: struct<mode: string, path: string, reason: string, sha256: string, size_bytes: int64, sou (... 13 chars omitted)
child 0, item: struct<mode: string, path: string, reason: string, sha256: string, size_bytes: int64, source: string (... 1 chars omitted)
child 0, mode: string
child 1, path: string
child 2, reason: string
child 3, sha256: string
child 4, size_bytes: int64
child 5, source: string
source_public_snapshot: struct<as_of_date: timestamp[s], checksum_index_sha256: string, manifest_sha256: string, payload_fil (... 69 chars omitted)
child 0, as_of_date: timestamp[s]
child 1, checksum_index_sha256: string
child 2, manifest_sha256: string
child 3, payload_file_count: int64
child 4, release_status: string
child 5, snapshot_content_ready: bool
upload_performed: bool
token_access: bool
to
{'builder': Value('string'), 'files': List({'mode': Value('string'), 'path': Value('string'), 'reason': Value('string'), 'sha256': Value('string'), 'size_bytes': Value('int64'), 'source': Value('string')}), 'integrity': {'algorithm': Value('string'), 'index': Value('string'), 'index_excludes': List(Value('string')), 'manifest_inventory_excludes': List(Value('string')), 'reason': Value('string')}, 'metadata_only': Value('bool'), 'network_access': Value('bool'), 'schema_version': Value('string'), 'source_public_snapshot': {'as_of_date': Value('timestamp[s]'), 'checksum_index_sha256': Value('string'), 'manifest_sha256': Value('string'), 'payload_file_count': Value('int64'), 'release_status': Value('string'), 'snapshot_content_ready': Value('bool')}, 'token_access': Value('bool'), 'upload_performed': Value('bool')}
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.
YAML Metadata Warning:The task_categories "video-question-answering" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other
AV-TRACE
AV-TRACE is a research project for diagnosing evidence acquisition, grounded generation, insufficiency recognition, stopping, and recovery in agentic long-video audiovisual RAG.
Current release status
This Hugging Face repository,
blackBOX25I47/videorag, is a metadata-only, pre-benchmark research
release. It does not currently contain a validated benchmark corpus or
redistributed source videos.
As of 2026-10-23:
H1 families = 0
H2 families = 0
Gate A = REPAIR
scientific episodes = 0
The repository therefore must not be described as a finished benchmark, human-gold dataset, or completed learned-agent evaluation.
What this repository contains
- project-authored research-state and migration metadata;
- public-safe provenance, policy, and reconstruction manifests;
- the post-migration CVPR work queue;
- integrity hashes for the corresponding public code snapshot;
- third-party data and redistribution notices.
What this repository does not contain
- raw or clipped third-party video/audio;
- EPIC-KITCHENS, CaptainCook4D, LongVideoBench, lecture, or NOAA payloads;
- model weights;
- dense private indexes or source-substitutive features;
- private reviewer identities, test-source identities, labels, or ledgers;
- credentials, authorization receipts, runtime attempts, or gateway output.
The absence of these files is intentional. A public or private Hugging Face repository does not override source licenses, consent, privacy, annotation authority, or redistribution restrictions.
Scientific scope
AV-TRACE uses the diagnostic stack:
Acquire -> Ground -> Act
and the matched states:
CLEAN / BLOCKED / RESTORED / NO_TRIGGER
The intended final corpus target is at least 60
H2_HUMAN_ADJUDICATED_SATURATION_AUDITED families from at least 30 source
groups, including at least 12 untouched test groups. These targets have not
yet been achieved.
Code
The public code repository is intended for:
https://github.com/HeRunming/videorag
Project-authored code and documentation are licensed under Apache-2.0. Third-party assets retain their own terms.
Data access and reconstruction
Where source-specific use is authorized, users should obtain third-party media and model assets directly from their official upstream locations at the pinned identities described in the manifests. AV-TRACE does not grant access to or redistribution rights for those assets.
Citation
No paper citation is frozen yet. Please cite the eventual AV-TRACE paper and release version once they are available. Until then, reference this repository as a research-in-progress metadata release.
Responsible use
Do not use project metadata to reconstruct private identities, bypass source access controls, infer untouched evaluation sources, or redistribute restricted media. Report licensing, privacy, or security concerns through the project repository's security contact.
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