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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type
struct<choice: string, ranking: list<item: string>>
to
{'choice': Value('string')}
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
struct<choice: string, ranking: list<item: string>>
to
{'choice': Value('string')}
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
prompt_id string | model string | ablation string | permutation int64 | mapping unknown | positions unknown | parse_ok bool | utc string | attempts list | image_count int64 | input_shapes dict | input_text_sha256 string | raw_output string | raw_output_sha256 string | parsed dict | selected_id string | seconds float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6 | qwen | choice_only | 0 | {
"A": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_SD35",
"B": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_flux",
"C": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_gpt-image"
} | {
"A": 0,
"B": 1,
"C": 2
} | true | 2026-09-30T14:10:09.186665+00:00 | [] | 3 | {
"input_ids": [
1,
768
],
"attention_mask": [
1,
768
],
"mm_token_type_ids": [
1,
768
],
"pixel_values": [
2352,
1536
],
"image_grid_thw": [
3,
3
]
} | b3798ddc94ce296a7e9399f4056ef88c488bed451414a30463fb4e2cb8cd1287 | {"choice": "A"} | 1d1fb135e3767b4fe105793442e925e8c764ea7932879d36d1b540a05ed1f5bf | {
"choice": "A"
} | e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_SD35 | 2.789351 |
e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6 | qwen | choice_only | 1 | {
"A": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_gpt-image",
"B": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_SD35",
"C": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_flux"
} | {
"A": 0,
"B": 1,
"C": 2
} | true | 2026-09-30T14:10:12.047359+00:00 | [] | 3 | {
"input_ids": [
1,
768
],
"attention_mask": [
1,
768
],
"mm_token_type_ids": [
1,
768
],
"pixel_values": [
2352,
1536
],
"image_grid_thw": [
3,
3
]
} | b3798ddc94ce296a7e9399f4056ef88c488bed451414a30463fb4e2cb8cd1287 | {"choice": "B"} | 2e3c8ffe211a9cc6125a9aa1ef4331853032c8ad434690d12e501245a8f85fe2 | {
"choice": "B"
} | e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_SD35 | 2.326627 |
e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6 | qwen | choice_only | 2 | {
"A": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_flux",
"B": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_gpt-image",
"C": "e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_SD35"
} | {
"A": 0,
"B": 1,
"C": 2
} | true | 2026-09-30T14:10:14.437455+00:00 | [] | 3 | {
"input_ids": [
1,
768
],
"attention_mask": [
1,
768
],
"mm_token_type_ids": [
1,
768
],
"pixel_values": [
2352,
1536
],
"image_grid_thw": [
3,
3
]
} | b3798ddc94ce296a7e9399f4056ef88c488bed451414a30463fb4e2cb8cd1287 | {"choice": "C"} | c0cbdb7f56bfd82845037d9c40a3d1eb6467cda121748f73adf5ccdea3af3fdb | {
"choice": "C"
} | e0512c6c7d0cbc5feecec014ce036cc75af0ebde9987eb039337c275460943a6_SD35 | 2.030667 |
b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71 | qwen | choice_only | 0 | {
"A": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_SD35",
"B": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_flux",
"C": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_gpt-image",
"D": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_... | {
"A": 0,
"B": 1,
"C": 2,
"D": 3
} | true | 2026-09-30T14:10:16.532825+00:00 | [] | 4 | {
"input_ids": [
1,
971
],
"attention_mask": [
1,
971
],
"mm_token_type_ids": [
1,
971
],
"pixel_values": [
3136,
1536
],
"image_grid_thw": [
4,
3
]
} | cec29b167f79feb6bb4f48170e021f96f433b8603fb584a85c1adcc6251c81f9 | {"choice": "A"} | 1d1fb135e3767b4fe105793442e925e8c764ea7932879d36d1b540a05ed1f5bf | {
"choice": "A"
} | b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_SD35 | 3.037355 |
b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71 | qwen | choice_only | 1 | {
"A": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_gpt-image",
"B": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_imagegen3",
"C": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_SD35",
"D": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d... | {
"A": 0,
"B": 1,
"C": 2,
"D": 3
} | true | 2026-09-30T14:10:19.664505+00:00 | [] | 4 | {
"input_ids": [
1,
971
],
"attention_mask": [
1,
971
],
"mm_token_type_ids": [
1,
971
],
"pixel_values": [
3136,
1536
],
"image_grid_thw": [
4,
3
]
} | cec29b167f79feb6bb4f48170e021f96f433b8603fb584a85c1adcc6251c81f9 | {"choice": "B"} | 2e3c8ffe211a9cc6125a9aa1ef4331853032c8ad434690d12e501245a8f85fe2 | {
"choice": "B"
} | b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_imagegen3 | 3.263244 |
b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71 | qwen | choice_only | 2 | {
"A": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_flux",
"B": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_gpt-image",
"C": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_imagegen3",
"D": "b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d... | {
"A": 0,
"B": 1,
"C": 2,
"D": 3
} | true | 2026-09-30T14:10:23.031506+00:00 | [] | 4 | {
"input_ids": [
1,
971
],
"attention_mask": [
1,
971
],
"mm_token_type_ids": [
1,
971
],
"pixel_values": [
3136,
1536
],
"image_grid_thw": [
4,
3
]
} | cec29b167f79feb6bb4f48170e021f96f433b8603fb584a85c1adcc6251c81f9 | {"choice": "C"} | c0cbdb7f56bfd82845037d9c40a3d1eb6467cda121748f73adf5ccdea3af3fdb | {
"choice": "C"
} | b10acf33f4e9b02c1049d8d92c32e1ec04a14e641e4bd8a928b5846e4d7d9c71_imagegen3 | 2.698765 |
712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3 | qwen | choice_only | 0 | {
"A": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_SD35",
"B": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_flux",
"C": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_gpt-image"
} | {
"A": 0,
"B": 1,
"C": 2
} | true | 2026-09-30T14:10:25.833932+00:00 | [] | 3 | {
"input_ids": [
1,
769
],
"attention_mask": [
1,
769
],
"mm_token_type_ids": [
1,
769
],
"pixel_values": [
2352,
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],
"image_grid_thw": [
3,
3
]
} | 450fe5c396acc4b4ba17f3b75008769ce6fc1788ef1c30bd916b360fc75cf225 | {"choice": "C"} | c0cbdb7f56bfd82845037d9c40a3d1eb6467cda121748f73adf5ccdea3af3fdb | {
"choice": "C"
} | 712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_gpt-image | 2.047322 |
712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3 | qwen | choice_only | 1 | {
"A": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_gpt-image",
"B": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_SD35",
"C": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_flux"
} | {
"A": 0,
"B": 1,
"C": 2
} | true | 2026-09-30T14:10:27.954176+00:00 | [] | 3 | {
"input_ids": [
1,
769
],
"attention_mask": [
1,
769
],
"mm_token_type_ids": [
1,
769
],
"pixel_values": [
2352,
1536
],
"image_grid_thw": [
3,
3
]
} | 450fe5c396acc4b4ba17f3b75008769ce6fc1788ef1c30bd916b360fc75cf225 | {"choice": "A"} | 1d1fb135e3767b4fe105793442e925e8c764ea7932879d36d1b540a05ed1f5bf | {
"choice": "A"
} | 712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_gpt-image | 2.171559 |
712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3 | qwen | choice_only | 2 | {
"A": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_flux",
"B": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_gpt-image",
"C": "712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_SD35"
} | {
"A": 0,
"B": 1,
"C": 2
} | true | 2026-09-30T14:10:30.192889+00:00 | [] | 3 | {
"input_ids": [
1,
769
],
"attention_mask": [
1,
769
],
"mm_token_type_ids": [
1,
769
],
"pixel_values": [
2352,
1536
],
"image_grid_thw": [
3,
3
]
} | 450fe5c396acc4b4ba17f3b75008769ce6fc1788ef1c30bd916b360fc75cf225 | {"choice": "B"} | 2e3c8ffe211a9cc6125a9aa1ef4331853032c8ad434690d12e501245a8f85fe2 | {
"choice": "B"
} | 712b735f188dcb8665054acd5b1f0897c326e28342172550e7c6f9735aae0aa3_gpt-image | 2.667777 |
5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b | qwen | choice_only | 0 | {
"A": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_SD35",
"B": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_flux",
"C": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_gpt-image",
"D": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_... | {
"A": 0,
"B": 1,
"C": 2,
"D": 3
} | true | 2026-09-30T14:10:32.927498+00:00 | [] | 4 | {
"input_ids": [
1,
977
],
"attention_mask": [
1,
977
],
"mm_token_type_ids": [
1,
977
],
"pixel_values": [
3136,
1536
],
"image_grid_thw": [
4,
3
]
} | a980ee016b5f4894925c3bd7453059f96512531f2db5c99787f0748ebee680ad | {"choice": "C"} | c0cbdb7f56bfd82845037d9c40a3d1eb6467cda121748f73adf5ccdea3af3fdb | {
"choice": "C"
} | 5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_gpt-image | 3.508679 |
5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b | qwen | choice_only | 1 | {
"A": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_imagegen3",
"B": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_SD35",
"C": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_flux",
"D": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_... | {
"A": 0,
"B": 1,
"C": 2,
"D": 3
} | true | 2026-09-30T14:10:36.554694+00:00 | [] | 4 | {
"input_ids": [
1,
977
],
"attention_mask": [
1,
977
],
"mm_token_type_ids": [
1,
977
],
"pixel_values": [
3136,
1536
],
"image_grid_thw": [
4,
3
]
} | a980ee016b5f4894925c3bd7453059f96512531f2db5c99787f0748ebee680ad | {"choice": "D"} | 7556fb1a1a3faf9184ad096a24196ccbb5b2968b2dd97486a1e889c183e33e8a | {
"choice": "D"
} | 5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_gpt-image | 3.459459 |
5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b | qwen | choice_only | 2 | {
"A": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_flux",
"B": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_gpt-image",
"C": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_imagegen3",
"D": "5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af... | {
"A": 0,
"B": 1,
"C": 2,
"D": 3
} | true | 2026-09-30T14:10:40.130294+00:00 | [] | 4 | {
"input_ids": [
1,
977
],
"attention_mask": [
1,
977
],
"mm_token_type_ids": [
1,
977
],
"pixel_values": [
3136,
1536
],
"image_grid_thw": [
4,
3
]
} | a980ee016b5f4894925c3bd7453059f96512531f2db5c99787f0748ebee680ad | {"choice": "B"} | 2e3c8ffe211a9cc6125a9aa1ef4331853032c8ad434690d12e501245a8f85fe2 | {
"choice": "B"
} | 5c291f96a2f1a39ec5a851e65bc16a443b739c9ce43b617a1b2326ec65af480b_gpt-image | 3.356293 |
8207f8d46ae89de25f3b92dcc75fb713da3db0229a8178ccb6be560bb94077f8 | qwen | choice_only | 0 | {
"A": "8207f8d46ae89de25f3b92dcc75fb713da3db0229a8178ccb6be560bb94077f8_SD35",
"B": "8207f8d46ae89de25f3b92dcc75fb713da3db0229a8178ccb6be560bb94077f8_flux",
"C": "8207f8d46ae89de25f3b92dcc75fb713da3db0229a8178ccb6be560bb94077f8_gpt-image"
} | {
"A": 0,
"B": 1,
"C": 2
} | true | 2026-09-30T14:10:43.590325+00:00 | [] | 3 | {
"input_ids": [
1,
768
],
"attention_mask": [
1,
768
],
"mm_token_type_ids": [
1,
768
],
"pixel_values": [
2352,
1536
],
"image_grid_thw": [
3,
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End of preview.
JudgeActs: recorded VLM selection decisions on culturally situated prompts
Data release for When the Judge Acts: Auditing VLM-Guided Image Selection on Culturally Situated Prompts (Huichan Seo).
- Project page: https://seochan99.github.io/JudgeActs/
- Code: https://github.com/seochan99/JudgeActs
A vision-language model judge chooses one of three or four generated images for each of 300 culturally situated prompts, under three cyclic presentation orders. Every choice is joined to released human ratings that the judge never saw.
Contents
| Config / file | Description |
|---|---|
pools |
300 frozen candidate pools: prompt, country, category, and per-candidate aggregated human ratings (prompt alignment, stereotype, missing explicit and implicit expectations, image quality, overall satisfaction) |
judge_calls |
Every recorded call for Qwen3-VL-4B-Instruct (900) and SmolVLM2-2.2B-Instruct (900): presentation mapping, raw output, parsed choice, validity flags, timing |
ablations |
Post-hoc Qwen runs: choice-only output format, opaque labels, and a fourth rotation for four-image pools |
scale_extension |
Qwen3-VL-8B (8-bit, MLX) on the same prompts and orders, plus an 8-bit Qwen3-VL-4B quantization control |
prompt_metrics |
Prompt-level outcomes for every policy (regret, gain over exact random choice, below-mean indicator, cultural-error ratings) |
results/ |
Every summary estimate reported in the paper, with bootstrap intervals |
manifests/ |
Frozen development, main, and reserve splits and presentation orders |
The key hsr in result files stores the below-mean rate (BMR) reported in the paper.
Images and ratings
Images are not included. Candidate ids match the public CulturalFrames release (Nayak et al., Findings of EMNLP 2025), from which images and the underlying annotations can be obtained under its terms. Aggregated ratings here are derived from that release; the CulturalFrames dataset card does not declare a license, so please respect its original terms. The judge outputs and analysis files are released under CC BY 4.0.
Citation
@misc{seo2026judgeacts,
title = {When the Judge Acts: Auditing VLM-Guided Image Selection on Culturally Situated Prompts},
author = {Seo, Huichan},
year = {2026},
note = {Preprint}
}
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