Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
concept_id: string
schema_version: string
task: string
benchmark_platform: string
env_id: string
benchmark_category: string
benchmark_category_index: int64
benchmark_fixed_target: bool
owner: string
identity_label: string
text: string
concrete_text: string
detailed_object_prompt: string
description: string
task_suite: list<item: struct<task_type: string, task_name: string, instruction_template: string, vap_env_family (... 377 chars omitted)
child 0, item: struct<task_type: string, task_name: string, instruction_template: string, vap_env_family: string, e (... 365 chars omitted)
child 0, task_type: string
child 1, task_name: string
child 2, instruction_template: string
child 3, vap_env_family: string
child 4, evaluation_protocol: struct<protocol_name: string, source_file: string, source_function: string, primary_success_field: s (... 201 chars omitted)
child 0, protocol_name: string
child 1, source_file: string
child 2, source_function: string
child 3, primary_success_field: string
child 4, correct_object_field: string
child 5, wrong_object_field: string
child 6, reported_info_fields: list<item: string>
child 0, item: string
child 7, thresholds: string
child 8, success_expression: string
child 9, cmr_definition: string
child 10, sr_definition: string
child 5, success_logic: string
child 6, fail_logic: string
tas
...
ldout_layout: int64
child 3, heldout_distractor: int64
child 4, heldout_density: int64
child 5, heldout_distractor_count: int64
child 4, extra_concept_level_view_cases: int64
child 5, total_expected_cases_per_concept: int64
child 6, note: string
child 7, heldout_types: list<item: string>
child 0, item: string
child 8, normal_anchor_per_scene: bool
child 9, distractor_count_values: list<item: int64>
child 0, item: int64
eval_case_ids: list<item: string>
child 0, item: string
object_bank: string
sticker_test: struct<base_source_model_id: string, target_sticker_model_id: string, plain_clone_model_ids: list<it (... 199 chars omitted)
child 0, base_source_model_id: string
child 1, target_sticker_model_id: string
child 2, plain_clone_model_ids: list<item: null>
child 0, item: null
child 3, single_face_decal: bool
child 4, camera_facing_target_yaw: bool
child 5, train_distractor_model_ids: list<item: string>
child 0, item: string
child 6, eval_distractor_model_ids: list<item: string>
child 0, item: string
child 7, camera_facing_per_core_object: bool
distractor_protocol: string
bench: string
distractor_split: struct<train_same_model_id: string, train_near_model_id: string, eval_same_model_id: string, eval_ne (... 36 chars omitted)
child 0, train_same_model_id: string
child 1, train_near_model_id: string
child 2, eval_same_model_id: string
child 3, eval_near_model_id: string
child 4, policy: string
to
{'concept_id': Value('string'), 'schema_version': Value('string'), 'task': Value('string'), 'benchmark_platform': Value('string'), 'env_id': Value('string'), 'benchmark_category': Value('string'), 'benchmark_category_index': Value('int64'), 'benchmark_fixed_target': Value('bool'), 'owner': Value('string'), 'identity_label': Value('string'), 'text': Value('string'), 'concrete_text': Value('string'), 'detailed_object_prompt': Value('string'), 'description': Value('string'), 'task_suite': List({'task_type': Value('string'), 'task_name': Value('string'), 'instruction_template': Value('string'), 'vap_env_family': Value('string'), 'evaluation_protocol': {'protocol_name': Value('string'), 'source_file': Value('string'), 'source_function': Value('string'), 'primary_success_field': Value('string'), 'correct_object_field': Value('string'), 'wrong_object_field': Value('string'), 'reported_info_fields': List(Value('string')), 'thresholds': Json(decode=True), 'success_expression': Value('string'), 'cmr_definition': Value('string'), 'sr_definition': Value('string')}, 'success_logic': Json(decode=True), 'fail_logic': Json(decode=True)}), 'task_count': Value('int64'), 'scene_style': Value('string'), 'scene_styles': List(Value('string')), 'target': {'model_id': Value('string'), 'category': Value('string'), 'role': Value('string')}, 'negative_objects': {'same_category': {'model_id': Value('string'), 'category': Value('string'), 'role': Value('string')}, 'near_category': {'model_id': Value('str
...
e('bool')}}), 'other_concept': List(Value('null'))}, 'vap_official_reference_root': Value('string'), 'vap_official_reference_paths': {'positive_examples': List(Value('null')), 'positive_examples_cropped': List(Value('null')), 'negative_examples': List(Value('null'))}, 'eval_case_count': Value('int64'), 'heldout_case_count': Value('int64'), 'expected_eval_case_count': Value('int64'), 'expected_heldout_case_count': Value('int64'), 'expected_task_eval_case_count': Value('int64'), 'heldout_design': {'episode_protocol': Value('string'), 'benchmark_mode': Value('string'), 'scene_axis': {'scene_styles': List(Value('string')), 'note': Value('string')}, 'cases_per_scene_breakdown': {'normal': Value('int64'), 'heldout_lighting': Value('int64'), 'heldout_layout': Value('int64'), 'heldout_distractor': Value('int64'), 'heldout_density': Value('int64'), 'heldout_distractor_count': Value('int64')}, 'extra_concept_level_view_cases': Value('int64'), 'total_expected_cases_per_concept': Value('int64'), 'note': Value('string'), 'heldout_types': List(Value('string')), 'normal_anchor_per_scene': Value('bool'), 'distractor_count_values': List(Value('int64'))}, 'eval_case_ids': List(Value('string')), 'object_bank': Value('string'), 'distractor_protocol': Value('string'), 'bench': Value('string'), 'distractor_split': {'train_same_model_id': Value('string'), 'train_near_model_id': Value('string'), 'eval_same_model_id': Value('string'), 'eval_near_model_id': Value('string'), 'policy': Value('string')}}
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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 343, 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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
concept_id: string
schema_version: string
task: string
benchmark_platform: string
env_id: string
benchmark_category: string
benchmark_category_index: int64
benchmark_fixed_target: bool
owner: string
identity_label: string
text: string
concrete_text: string
detailed_object_prompt: string
description: string
task_suite: list<item: struct<task_type: string, task_name: string, instruction_template: string, vap_env_family (... 377 chars omitted)
child 0, item: struct<task_type: string, task_name: string, instruction_template: string, vap_env_family: string, e (... 365 chars omitted)
child 0, task_type: string
child 1, task_name: string
child 2, instruction_template: string
child 3, vap_env_family: string
child 4, evaluation_protocol: struct<protocol_name: string, source_file: string, source_function: string, primary_success_field: s (... 201 chars omitted)
child 0, protocol_name: string
child 1, source_file: string
child 2, source_function: string
child 3, primary_success_field: string
child 4, correct_object_field: string
child 5, wrong_object_field: string
child 6, reported_info_fields: list<item: string>
child 0, item: string
child 7, thresholds: string
child 8, success_expression: string
child 9, cmr_definition: string
child 10, sr_definition: string
child 5, success_logic: string
child 6, fail_logic: string
tas
...
ldout_layout: int64
child 3, heldout_distractor: int64
child 4, heldout_density: int64
child 5, heldout_distractor_count: int64
child 4, extra_concept_level_view_cases: int64
child 5, total_expected_cases_per_concept: int64
child 6, note: string
child 7, heldout_types: list<item: string>
child 0, item: string
child 8, normal_anchor_per_scene: bool
child 9, distractor_count_values: list<item: int64>
child 0, item: int64
eval_case_ids: list<item: string>
child 0, item: string
object_bank: string
sticker_test: struct<base_source_model_id: string, target_sticker_model_id: string, plain_clone_model_ids: list<it (... 199 chars omitted)
child 0, base_source_model_id: string
child 1, target_sticker_model_id: string
child 2, plain_clone_model_ids: list<item: null>
child 0, item: null
child 3, single_face_decal: bool
child 4, camera_facing_target_yaw: bool
child 5, train_distractor_model_ids: list<item: string>
child 0, item: string
child 6, eval_distractor_model_ids: list<item: string>
child 0, item: string
child 7, camera_facing_per_core_object: bool
distractor_protocol: string
bench: string
distractor_split: struct<train_same_model_id: string, train_near_model_id: string, eval_same_model_id: string, eval_ne (... 36 chars omitted)
child 0, train_same_model_id: string
child 1, train_near_model_id: string
child 2, eval_same_model_id: string
child 3, eval_near_model_id: string
child 4, policy: string
to
{'concept_id': Value('string'), 'schema_version': Value('string'), 'task': Value('string'), 'benchmark_platform': Value('string'), 'env_id': Value('string'), 'benchmark_category': Value('string'), 'benchmark_category_index': Value('int64'), 'benchmark_fixed_target': Value('bool'), 'owner': Value('string'), 'identity_label': Value('string'), 'text': Value('string'), 'concrete_text': Value('string'), 'detailed_object_prompt': Value('string'), 'description': Value('string'), 'task_suite': List({'task_type': Value('string'), 'task_name': Value('string'), 'instruction_template': Value('string'), 'vap_env_family': Value('string'), 'evaluation_protocol': {'protocol_name': Value('string'), 'source_file': Value('string'), 'source_function': Value('string'), 'primary_success_field': Value('string'), 'correct_object_field': Value('string'), 'wrong_object_field': Value('string'), 'reported_info_fields': List(Value('string')), 'thresholds': Json(decode=True), 'success_expression': Value('string'), 'cmr_definition': Value('string'), 'sr_definition': Value('string')}, 'success_logic': Json(decode=True), 'fail_logic': Json(decode=True)}), 'task_count': Value('int64'), 'scene_style': Value('string'), 'scene_styles': List(Value('string')), 'target': {'model_id': Value('string'), 'category': Value('string'), 'role': Value('string')}, 'negative_objects': {'same_category': {'model_id': Value('string'), 'category': Value('string'), 'role': Value('string')}, 'near_category': {'model_id': Value('str
...
e('bool')}}), 'other_concept': List(Value('null'))}, 'vap_official_reference_root': Value('string'), 'vap_official_reference_paths': {'positive_examples': List(Value('null')), 'positive_examples_cropped': List(Value('null')), 'negative_examples': List(Value('null'))}, 'eval_case_count': Value('int64'), 'heldout_case_count': Value('int64'), 'expected_eval_case_count': Value('int64'), 'expected_heldout_case_count': Value('int64'), 'expected_task_eval_case_count': Value('int64'), 'heldout_design': {'episode_protocol': Value('string'), 'benchmark_mode': Value('string'), 'scene_axis': {'scene_styles': List(Value('string')), 'note': Value('string')}, 'cases_per_scene_breakdown': {'normal': Value('int64'), 'heldout_lighting': Value('int64'), 'heldout_layout': Value('int64'), 'heldout_distractor': Value('int64'), 'heldout_density': Value('int64'), 'heldout_distractor_count': Value('int64')}, 'extra_concept_level_view_cases': Value('int64'), 'total_expected_cases_per_concept': Value('int64'), 'note': Value('string'), 'heldout_types': List(Value('string')), 'normal_anchor_per_scene': Value('bool'), 'distractor_count_values': List(Value('int64'))}, 'eval_case_ids': List(Value('string')), 'object_bank': Value('string'), 'distractor_protocol': Value('string'), 'bench': Value('string'), 'distractor_split': {'train_same_model_id': Value('string'), 'train_near_model_id': Value('string'), 'eval_same_model_id': Value('string'), 'eval_near_model_id': Value('string'), 'policy': Value('string')}}
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.
Concept held-out distractors (ab train / cd eval)
Personalization training + eval packages for Sticker-SIMPLER and PVLA-SIMPLER.
Protocol
- Train negatives:
a/b(train_same/train_near) - Eval negatives:
c/d(eval_same/eval_near) - Policy:
train_ab_eval_cd
Layout
| Path | Domain | Concepts | Notes |
|---|---|---|---|
sticker/ |
Sticker-SIMPLER | 13 | train.jsonl, refs, crops, masks, eval/task_eval |
pvla/ |
PVLA-SIMPLER | 11 | same layout |
Key files per domain:
train.jsonl— personalization training recordsimages/references/— positive / negative reference viewsmasks/references/— reference masks +manifest.json(VAP/F3RM)crops/— cropped refseval.jsonl,task_eval.jsonl— held-out eval / rollout cases
Local source
outputs/concept_heldout_distractors_20260727/{sticker,pvla}
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