---
pretty_name: Visual Answerability across Charts and Scenes
language:
- en
license: other
license_name: component-specific-see-license
license_link: LICENSE.md
task_categories:
- visual-question-answering
size_categories:
- 10K<n<100K
tags:
- visual-answerability
- abstention
- executable-certificates
- plotqa
- clevr
- gqa
configs:
- config_name: plotqa
  default: true
  data_files:
  - split: test
    path: data/plotqa/*.parquet
- config_name: clevr
  data_files:
  - split: test
    path: data/clevr/*.parquet
- config_name: gqa
  data_files:
  - split: test
    path: data/gqa/*.parquet
---

# Visual Answerability across Charts and Scenes

Frozen release: **answerability-v1.0.0-20260928**, Hub tag **v1.0.0**.
Dataset: [sungguk/visual-answerability](https://huggingface.co/datasets/sungguk/visual-answerability).
This benchmark accompanies *When Does an Image Determine the Answer?
Benchmarking Visual Answerability across Charts and Scenes*, using the
September 28, 2026 manuscript metadata and the unchanged evaluated cohorts.
No arXiv identifier or DOI has been assigned in this package.

Each source question has several original/edited views. Present **one image and
one question independently** to a model; group responses only after inference.
The main task requires correct supported answers and correct abstentions for
every view of a question. Do not expose `state`, `target`, `answerable`, sibling
views, or evidence files to the model.

## Contents and access

| Configuration | Groups / views | Image access |
|---|---|---|
| `plotqa` | 1,000 / 5,000 | Embedded PNG |
| `clevr` | 1,000 / 4,000 | Embedded PNG |
| `gqa` | 1,000 / 3,000 | Local reconstruction |

All three configurations use an evaluation-only `test` split. Source splits
remain explicit: PlotQA comes from the frozen train-prefix selection; CLEVR and
GQA come from source validation data. This naming does not imply use of an
official upstream hidden test split. This release covers the **12,000 evaluated
views**, not the broader 58,000-view training/development resource.

The chart cohort uses executable D15 direct-lookup questions from the frozen
PlotQA prefix. CLEVR uses source functional programs; GQA uses the supported
native semantic-program subset. There is one source image per question group
within each domain.

The `gqa` configuration supplies IDs, our labels and edit recipes. Its `image`
and `question` fields are null. The official GQA pages and archive READMEs checked
for this preparation did not supply an explicit annotation redistribution grant.
The earlier local CC BY declaration is not treated as upstream permission.
Obtain the official questions, graphs and images yourself, then follow
[RECONSTRUCTION.md](RECONSTRUCTION.md). The reconstruction checks source identity,
programs, labels and exact evaluated image bytes. It writes outside this folder.

PlotQA and CLEVR data retain CC BY 4.0; bundled project code retains Apache 2.0.
See [LICENSE.md](LICENSE.md) and [ATTRIBUTION.md](ATTRIBUTION.md) for component
boundaries, upstream authors, modifications and notices.

## Load the dataset

```bash
python -m pip install datasets pillow
```

```python
from datasets import load_dataset

root = "sungguk/visual-answerability"
charts = load_dataset(root, "plotqa", split="test", revision="v1.0.0")
scenes = load_dataset(root, "clevr", split="test", revision="v1.0.0")
gqa_index = load_dataset(root, "gqa", split="test", revision="v1.0.0")
example = charts[0]
example["image"].save("example.png")
print(example["question"])
```

For the evidence, scoring scripts and pinned dependencies, download the full
snapshot as described in [UPLOAD.md](UPLOAD.md). The `v1.0.0` tag identifies the
verified release commit; use that commit hash when an immutable revision is
required. Local snapshot paths can also be passed to `load_dataset`.

## Fields and states

`item_id` is the stable prediction join key (`item-0001`… or `cross-00000`…).
`group_id` joins sibling states. `source_question_id`, `source_image_id`,
`source_split`, and `source_revision` preserve upstream identity.
`question_sha256` and `image_sha256` validate reconstruction and release
integrity; hashes are not the semantic proof of a label. `image` is a Hugging
Face Image feature backed by embedded bytes, except for GQA. `target` is a
string, with `<UNANSWERABLE>` for unanswerable states. `dependency_depth` is the
historical field name; for scene programs it counts steps, not tree depth.

- `FULL`: the original supported question.
- `A_SAME`: a control edit preserves the supported answer.
- `A_CHANGED`: an edit changes the supported answer (charts and CLEVR).
- `U_MISSING`: the construction removes evidence needed for a unique answer.
- `U_INVALID`: an edit invalidates the chart question's referent (charts only).

`evidence_kind`, `evidence_file`, `operator`, `source_view_id`, and
`gqa_location_stratum` describe the construction and its evidence. The location
flag identifies 376 GQA groups for the paper's sensitivity analysis; it is not
a finding that those labels are wrong or that the remaining 624 groups are clean.

## Evidence and evaluation

- **Chart proofs:** `evidence/plotqa/bounded-witness-proofs.jsonl.gz` contains
  all 1,000 corrected bounded witnesses, reconstructed from frozen FULL and
  A_CHANGED worlds and verified against each evaluated missing-view PNG.
  The checker re-renders complete worlds, verifies axis admissibility and two
  executors, then checks identical intervened pixels with different answers.
  These are freshly serialized proofs, not a claim of byte identity with an
  unavailable historical proof archive.
  Original per-view certificate descriptors are retained as historical
  construction metadata. The corrected chart missing-information claim is
  verified from the separate bounded-witness records above.
- **Scene evidence:** CLEVR programs, worlds, alternatives and render/edit
  metadata are in `evidence/clevr/`. GQA source evidence is reconstructed from
  official inputs using `evidence/gqa/reconstruction.jsonl.gz`. Neither scene
  subset is presented as having the chart complete-world pixel guarantee.
- **Scoring records:** `inputs/` contains six configurations' 72,000 selected
  final scoring projections, including 11 terminal invalid outputs. These are
  parsed scoring fields, not raw generations, token traces or fresh inference.
  GQA question text is replaced by stable question-ID references; its rationale
  text is omitted. Scoring and all reported numerical results are preserved.
  Image paths inside the historical scoring manifests and group descriptors
  describe the original construction layout; use the Parquet `image` column
  and stable `item_id` for public model inputs.
- **Statistics:** exact replay of all 18 model/domain cells and 10,000-draw
  paired group bootstrap intervals; also saved finite-program records for
  1,024 original and 1,456 combined solver-study cases. Replaying these records
  is separate from rerunning the solver constructors.

See [EVALUATION.md](EVALUATION.md) for new predictions and replay commands,
[PROTOCOL.md](PROTOCOL.md) for prompts and serving configurations, and
[UPLOAD.md](UPLOAD.md) for snapshot download and release verification.

## Intended use and limitations

Use for evaluation of image-conditioned answers and abstention, construction
audits, and reproduction of reported analyses. Do not train or tune on this
evaluation split when reporting its benchmark results. Questions were selected
by deterministic executable-program and rendering gates, not representative
sampling of all visual questions. New per-example edits/labels used no human
adjudication or reasoning-model judgments.

The chart claim assumes correct source truth, question/program compilation,
the fixed-axis rational-valued world class, and the drawing primitives. The
two executors are independent implementations; they share rendering code.
CLEVR labels use source programs and edits. GQA graphs and object boxes may be
incomplete; position questions can retain visible cues. Report GQA scores as
agreement with these source-derived labels, including both sensitivity strata.
There is no independent human adjudication of every view. Configuration
comparisons include different serving backends; Qwen 27B scenes mix preserved
API outputs and a local FP8 fallback. Intervals are descriptive, paired by
question, and not corrected for multiple comparisons.

Upstream photographs may depict people and everyday places. The release adds
no identity annotation or sensitive-attribute classification. All original
rights and any third-party rights remain with their respective holders.

## Citation and provenance

Use [CITATION.cff](CITATION.cff) or [CITATION.bib](CITATION.bib), and cite the
upstream datasets in [ATTRIBUTION.md](ATTRIBUTION.md). The author list follows
the prepared manuscript; no conference acceptance or published identifier is
asserted. `RELEASE.json` records the build scope and source snapshot.
`MANIFEST.json` identifies every frozen file, including the actual working-tree
code used despite existing uncommitted manuscript revisions. Reports under
`validation/` state what was actually checked during local preparation. Their
historical `publication_performed: false` fields describe those offline checks,
not the current Hub visibility. The release retains the exact evaluated data,
proofs, scoring records and software of the frozen preparation candidate.