Add dataset card: intro, examples, task table, evaluation protocol, headline results

README.md

@@ -0,0 +1,110 @@
+---
+pretty_name: ActiveVision
+license: cc-by-4.0
+language:
+- en
+task_categories:
+- visual-question-answering
+- image-text-to-text
+tags:
+- benchmark
+- visual-reasoning
+- iterative-reasoning
+- active-vision
+- multimodal
+- vqa
+- evaluation
+size_categories:
+- n<1K
+---
+
+<p align="center">
+  <img src="assets/banner.png" alt="ActiveVision — An Exam for Active Observers. Vision is a loop, not a glance." width="820">
+</p>
+
+# ActiveVision — An Exam for Active Observers
+
+**ActiveVision** is a benchmark for **iterative visual reasoning**: 85 photorealistic
+items across **17 tasks** that cannot be solved from a single glance — the model has
+to keep returning to the image to *scan*, *trace*, and *compare*. Every scene is
+generated by a deterministic program and re-rendered photorealistically while
+preserving the structure, so answers are exact by construction.
+
+**Frontier models reach about 10%** with pure chain-of-thought (50.6% with an
+autonomous coding agent), while **unaided humans average 96.1%**.
+
+🌐 [Website](https://activevision.dev) · 📄 Paper: coming soon · 💻 Evaluation code: coming soon
+
+## Examples
+
+<table>
+<tr>
+<td width="50%" align="center"><img src="assets/example_traverse.jpg" alt="Traversal point ordering example" width="420"></td>
+<td width="50%" align="center"><img src="assets/example_regions.jpg" alt="Region counting example" width="420"></td>
+</tr>
+</table>
+
+## The 17 tasks
+
+| Family | Tasks |
+|---|---|
+| **Distributed Scanning** — find and count every signal | bounded_face_counting · connected_component_counting · region_counting · singleton_shape_counting · tangled_loop_counting |
+| **Sequential Traversal** — follow a structure, step by step | arrow_chain_following · color_zone_sequencing · line_intersection_sequencing · maze_path_tracing · traversal_point_ordering |
+| **Visual Attribute Transfer** — compare a property across regions | constellation_match_counting · contour_difference_spotting · field_difference_spotting · signal_difference_spotting · silhouette_match_counting · stroke_difference_spotting · stroke_match_counting |
+
+5 items per task, 85 items total. Each item is **one still image and one question**;
+answers are integers, letters, or ordered sequences — never small multiple choice, so
+the guess floor is near zero.
+
+## Dataset structure
+
+```python
+from datasets import load_dataset
+ds = load_dataset("activevisionai/ActiveVision", split="train")
+# columns: image, id, task, category, question, answer
+```
+
+| Field | Description |
+|---|---|
+| `image` | the photorealistic scene (PNG, up to 1536×1024) |
+| `id` | item id, `<TASK-PREFIX>-<index>` (e.g. `MPT-2`) |
+| `task` | one of the 17 task names above |
+| `category` | task family: `distributed_scanning`, `sequential_traversal`, `visual_attribute_transfer` |
+| `question` | the full question, instructing the model to answer in `<answer>...</answer>` tags |
+| `answer` | ground truth (exact-match scoring, separator-insensitive) |
+
+## Evaluation
+
+Score the contents of the model's **last** `<answer>...</answer>` block by exact
+match after normalizing case, whitespace, and separators (`"C, A, G"` ≡ `"CAG"`;
+integer answers also match numerically, `"07"` ≡ `7`).
+
+## Headline results (pure chain-of-thought, best per model)
+
+| Model | Accuracy |
+|---|---|
+| Human (N=3, unaided) | **96.1%** |
+| GPT-5.5 (xhigh) | 10.6% |
+| Gemini 3.5 Flash (high) | 8.2% |
+| Gemini 3.1 Pro (high) | 5.9% |
+| Claude Opus 4.7 (max) | 4.7% |
+| Claude Fable 5 (max) | 3.5% |
+
+![Accuracy vs API cost per item across reasoning-effort tiers](assets/performance_cost.png)
+
+More reasoning does not close the gap: scaling effort moves models along the cost
+axis, not toward the human band. Tool-using coding agents reach at most 50.6%
+(Claude Code, Fable 5) at $2.74–$7.63 and 12–15 minutes per item — a human answers
+unaided in 34 seconds.
+
+## Citation
+
+```bibtex
+@article{zhang2026activevision,
+  title   = {An Exam for Active Observers},
+  author  = {Zhang, Jiarui and Tao, Muzi and Wang, Shangshang and Liu, Ollie and Ma, Xuezhe and Neiswanger, Willie},
+  journal = {arXiv preprint},
+  year    = {2026},
+  note    = {Coming soon}
+}
+```