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1 Parent(s): 8a0e00a

Publish dataset card, configuration loader and verified artifact manifest

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ARTIFACT_MANIFEST.json ADDED
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1
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65
+ }
README.md CHANGED
@@ -4,39 +4,87 @@ tags:
4
  - text-to-image
5
  - cultural-values
6
  - evaluation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7
  ---
8
 
9
  # VisionValueBench
10
 
11
- VisionValueBench studies visual value leakage in text-to-image generation. Prompts, decision materials, and numerical reproduction are available in the [GitHub repository](https://github.com/zucanlv/VisionValueBench).
 
12
 
13
- ## Current status
14
 
15
- This public dataset repository is being prepared. Images, rich annotations, and numerical labels have not been uploaded. The frozen numerical labels have been validated locally; this repository does not yet contain a usable dataset. Image provenance, source manifests, licensing, and reader compatibility remain to be checked before publication.
16
 
17
- ## Planned scope
18
 
19
- The frozen analysis contains **68,764 completed image IDs** across eight configurations: six base generators and two extensions (FLUX Upsampler and HiDream Refiner). The design target was **69,120**, leaving 356 incomplete records outside the frozen analysis.
 
 
 
 
 
 
 
 
 
20
 
21
- | Configuration | Design target | Frozen complete IDs |
22
- | --- | ---: | ---: |
23
- | FLUX.2 | 5,760 | 5,760 |
24
- | FLUX.2 Upsampler | 5,760 | 5,760 |
25
- | GPT Image 2 | 13,440 | 13,243 |
26
- | HiDream | 5,760 | 5,760 |
27
- | HiDream Refiner | 5,760 | 5,760 |
28
- | Ideogram 4 Magic | 5,760 | 5,753 |
29
- | MAI 2.6 Flash | 13,440 | 13,302 |
30
- | NanoBanana 2 | 13,440 | 13,426 |
31
- | **Total** | **69,120** | **68,764** |
32
 
33
- Evaluation images will preserve the actual bytes submitted to the automatic judges, matched to frozen IDs and verified provenance. Original generated images may be added separately after their relationship to the evaluation images is checked.
34
 
35
- Annotations will retain **Scenario-Anticipated Evaluation (SAE)** and **Image-Adaptive Evaluation (IAE)** separately. Each method has three judges providing 12 binary endpoint votes per image. Each endpoint's majority requires at least two supporting judges. Rich evidence will be exported only after its schema and public fields are verified.
36
 
37
- ## Files currently available
38
 
39
- - `dataset_status.json`: preparation status and expected counts.
40
- - `UPLOAD_PLAN.md`: remaining verification and upload steps.
 
 
 
 
41
 
42
- Licensing and the final storage layout will be documented after source review.
 
 
 
 
 
 
 
4
  - text-to-image
5
  - cultural-values
6
  - evaluation
7
+ configs:
8
+ - config_name: all
9
+ default: true
10
+ data_files:
11
+ - split: test
12
+ path: data/*/*.parquet
13
+ - config_name: flux2
14
+ data_files:
15
+ - split: test
16
+ path: data/flux2/*.parquet
17
+ - config_name: flux2_upsampler
18
+ data_files:
19
+ - split: test
20
+ path: data/flux2_upsampler/*.parquet
21
+ - config_name: gptimage2
22
+ data_files:
23
+ - split: test
24
+ path: data/gptimage2/*.parquet
25
+ - config_name: hidream
26
+ data_files:
27
+ - split: test
28
+ path: data/hidream/*.parquet
29
+ - config_name: hidream_refiner
30
+ data_files:
31
+ - split: test
32
+ path: data/hidream_refiner/*.parquet
33
+ - config_name: ideogram4_magic
34
+ data_files:
35
+ - split: test
36
+ path: data/ideogram4_magic/*.parquet
37
+ - config_name: mai26flash
38
+ data_files:
39
+ - split: test
40
+ path: data/mai26flash/*.parquet
41
+ - config_name: nanobanana2
42
+ data_files:
43
+ - split: test
44
+ path: data/nanobanana2/*.parquet
45
  ---
46
 
47
  # VisionValueBench
48
 
49
+ VisionValueBench studies visual value leakage in multilingual text-to-image generation.
50
+ [Project homepage](https://zucanlv.github.io/VisionValueBench/) · [Code and execution prompts](https://github.com/zucanlv/VisionValueBench)
51
 
52
+ ## Scope
53
 
54
+ This package contains 68,764 evaluation-image records. The frozen benchmark contains 68,764 completed IDs against a design target of 69,120 across six base generators and two extensions.
55
 
56
+ Evaluation JPEG bytes are preserved exactly as submitted to the automatic judges and checked against recorded review-image hashes. Scenario text and frozen numerical labels accompany each image. Final annotation files contain binary votes and decisions; this package does not include rich evidence responses or original generated images.
57
 
58
+ | Configuration | Records |
59
+ | --- | ---: |
60
+ | `flux2` | 5,760 |
61
+ | `flux2_upsampler` | 5,760 |
62
+ | `gptimage2` | 13,243 |
63
+ | `hidream` | 5,760 |
64
+ | `hidream_refiner` | 5,760 |
65
+ | `ideogram4_magic` | 5,753 |
66
+ | `mai26flash` | 13,302 |
67
+ | `nanobanana2` | 13,426 |
68
 
69
+ ## Fields and judgments
 
 
 
 
 
 
 
 
 
 
70
 
71
+ `sample_id`, `model_configuration`, `scenario_id`, `prompt_language`, `culture_cue`, and `six_shared_conditions` identify each scientific condition. `scenario` holds the English scenario context supplied to the evaluators; it is not the translated generation prompt. `image` contains embedded image bytes with a relative sample filename; `evaluation_sha256`, `image_width`, and `image_height` describe those bytes.
72
 
73
+ SAE (Scenario-Anticipated Evaluation) and IAE (Image-Adaptive Evaluation) remain separate. Each method has three judges (`luna`, `gemini`, `muse`) and 12 binary endpoint votes. `sae_votes` and `iae_votes` retain each judge's vector; `sae_supported` and `iae_supported` are per-endpoint majorities (at least two supporting judges). Opposing orientations are judged independently. See `dataset_spec.json` for endpoint order and judge model names.
74
 
75
+ ## Load
76
 
77
+ ```python
78
+ from datasets import load_dataset
79
+ dataset = load_dataset("ZucanLyu/VisionValueBench", "all", split="test", streaming=True)
80
+ row = next(iter(dataset))
81
+ image = row["image"]
82
+ ```
83
 
84
+ The `test` split names the evaluation collection; it does not imply an independent training/test partition. Each named configuration selects its own shards; `all` references the same files without duplicating records.
85
+
86
+ The same numerical labels are available separately in `labels.jsonl.gz` for analyses that do not need image downloads.
87
+
88
+ ## Verification and availability
89
+
90
+ `ARTIFACT_MANIFEST.json` records shard hashes, sizes, row counts, and image-byte totals. `BUILD_STATUS.json` records local build/readback checks. Repository access and viewer availability depend on the current Hub settings. Licensing has not been specified.
UPLOAD_PLAN.md CHANGED
@@ -1,8 +1,3 @@
1
- # Upload plan
2
 
3
- 1. Verify the three final source manifests against the frozen unique ID set and per-configuration counts. Inspect the rich annotation schema and confirm full judge model names.
4
- 2. Match each evaluation image to its actual judge input using verified provenance and content hashes. Measure this selected dataset; document original-image relationships separately.
5
- 3. Export only approved public fields. Preserve SAE and IAE votes and majorities separately. Resolve licensing and document endpoint order and configuration definitions.
6
- 4. Choose shards after measuring the data. Validate member hashes, label alignment, extraction, and a working reader/viewer. Upload the verified data to this public repository after these checks are complete.
7
-
8
- The current initialization includes documentation only. Numerical labels remain local, and no images or rich annotations have been uploaded.
 
1
+ # Publication status
2
 
3
+ The core evaluation dataset is published: 68,764 images across eight configurations, with frozen numerical SAE/IAE votes and majorities. Image bytes and labels passed complete source comparison and Parquet readback. All remote shard hashes match the artifact manifest. Original generated-image archival is tracked separately.
 
 
 
 
 
dataset_spec.json ADDED
@@ -0,0 +1,167 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "sample_count": 68764,
3
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+ "nanobanana2": 13426
12
+ },
13
+ "design_target_image_ids": 69120,
14
+ "endpoint_order": [
15
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