| --- |
| configs: |
| - config_name: combined_eval5 |
| default: true |
| data_files: |
| - split: test |
| path: |
| - parquet/section1/test-*.parquet |
| - parquet/section2/test-*.parquet |
| - config_name: section1_eval5 |
| data_files: |
| - split: test |
| path: parquet/section1/test-*.parquet |
| - config_name: section2_eval5 |
| data_files: |
| - split: test |
| path: parquet/section2/test-*.parquet |
| task_categories: |
| - visual-question-answering |
| tags: |
| - synthetic |
| - visual-question-answering |
| - evaluation |
| - parquet |
| --- |
| |
| # PixelProof Evaluation |
|
|
| The frozen evaluation sets for the PixelProof paper. Each eligible |
| replay-verified world contributes exactly five deterministic, pixel-distinct |
| instances. The five instances of a world share its selected question text but show different rendered scenes; the answer can differ between instances, and the world's inverse program recovers it from the image alone. |
|
|
| | Config | Experiment | Worlds | Instances | Documented exclusions | |
| |---|---|---:|---:|---:| |
| | `section1_eval5` | Profile-steered generation | 1,298 | 6,490 | 3 | |
| | `section2_eval5` | Spatially-steered generation | 874 | 4,370 | 1 | |
| | `combined_eval5` | Both experiments | 2,172 | 10,860 | 4 | |
|
|
| The config names, the `section` column, and the `ledgers/section*` files are |
| stable identifiers: `section1` holds profile-steered worlds and `section2` |
| holds spatially-steered worlds. The exclusions are the worlds that passed the |
| 200-scene replay (1,301 profile-steered and 875 spatially-steered) but |
| produced fewer than five pixel-distinct scenes; each one is documented in the |
| corresponding `ledgers/section*_exclusions.csv` file. |
|
|
| Each row exposes a native `image`, `question`, `answer`, `answer_options`, a |
| stable `evaluation_id`, `instance_rank`, an image hash, coding-agent provenance, |
| the discovery profile, and verification metadata. Spatially-steered rows also |
| record their spatial pattern (`pixel_support_scale`, `pixel_support_shape`, |
| and `pixel_diversity_cell`), one of nine patterns that combine a scale |
| (focal, regional, distributed) with a shape (compact, pathlike, multipart). |
| These columns are empty for profile-steered rows. |
|
|
| ## Keeping answers out of prompts |
|
|
| The dataset includes `answer` for scoring. A model request must use only |
| `image`, `question`, and `answer_options`; do not serialize the full row into |
| the prompt. For stricter orchestration, use the answer-free and answer-only CSV ledgers under `ledgers/`, whose source hashes are frozen in |
| `manifests/source-sections.json`. |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("PixelProof/PixelProof-Evaluation", "section1_eval5", split="test") |
| row = ds[0] |
| row["image"].show() |
| print(row["question"], row["answer_options"], row["answer"]) |
| ``` |
|
|
| ## Release integrity |
|
|
| This release preserves the questions, answers, images, and dataset |
| configurations used in the paper. Local filesystem paths in audit diagnostics |
| are redacted, and `CHECKSUMS.sha256` lists SHA-256 checksums for the files |
| distributed here. |
|
|
| ## Project resources |
|
|
| - [PixelProof website](https://projectpixelproof.github.io/) |
| - [Source code](https://github.com/ProjectPixelProof/PixelProof) |
|
|
