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README.md

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+---
+pretty_name: PlayWorld Benchmark
+language:
+- en
+task_categories:
+- visual-question-answering
+size_categories:
+- n<1K
+tags:
+- world-model
+- video-generation
+- interactive-agents
+- benchmark
+- long-horizon-evaluation
+configs:
+- config_name: gc
+  data_files: gc/data.json
+- config_name: if
+  data_files: if/data.json
+- config_name: insight
+  data_files: insight/data.json
+- config_name: outsight
+  data_files: outsight/data.json
+---
+
+# PlayWorld: Benchmarking World Models with Agent Players over Long-Horizon Objectives
+
+Anonymous benchmark release for double-blind review. Author, affiliation, and
+identity-bearing links are intentionally omitted.
+
+[**Project**](https://playworld-2026.github.io/project/PlayWorld/) | [**Code**](../code/)
+
+Video world models generate future states from an initial observation and user
+actions. Comparing interactive models fairly is difficult because the actions
+required to reach the same long-horizon objective can vary substantially across
+models.
+
+PlayWorld evaluates world models from the perspective of a human player. Each
+case provides an initial world, a scene-grounded long-horizon objective, a
+human-annotated basic action sequence, and a sample-specific VQA rubric. During
+evaluation, a multi-modal **Agent Player** observes generated frames and adapts
+action execution toward the objective. This dataset provides the initial worlds,
+objectives, basic action sequences, and rubrics used by that protocol.
+
+## Benchmark Overview
+
+PlayWorld contains 171 human-annotated cases and 820+ sample-specific VQA
+questions across four core world-model capabilities:
+
+- **Geometry Consistency (GC):** whether object identity, appearance, relative
+  position, and scene layout remain consistent during camera movement and
+  revisitation.
+- **Interaction Fidelity (IF):** whether a controlled subject reaches and
+  interacts with the intended region through plausible contact, collision,
+  motion, causal response, and visual feedback.
+- **Insight Evolution (IE):** whether a continuously observed subject or process
+  exhibits coherent state progression, physically plausible motion, and
+  temporally consistent surroundings.
+- **Out-of-sight Evolution (OE):** whether a target preserves its identity and
+  continues to evolve plausibly while outside the field of view, with a
+  causally consistent state when revealed again.
+
+The questions cover four broad evidence families: identity and appearance,
+physics and dynamics, temporal evolution, and spatial and trajectory reasoning.
+Rubrics are tailored to each scene so that only observable and applicable
+criteria are evaluated.
+
+## Dataset Composition
+
+| Config | Evaluation dimension | Source IDs | Cases |
+| --- | --- | --- | ---: |
+| `gc` | Geometry Consistency | `GCxxx` | 48 |
+| `if` | Interaction Fidelity | `IFxxx` | 50 |
+| `insight` | Insight Evolution | `OExxx` | 30 |
+| `outsight` | Out-of-sight Evolution | `OExxx` | 43 |
+| **Total** |  |  | **171** |
+
+Insight and out-of-sight cases retain their original `OExxx` task IDs and image
+filenames. IDs are not renumbered after the two evaluation settings are placed
+in separate configs.
+
+Initial worlds cover natural, urban, indoor, and imaginative environments, with
+human, animal, vehicle, object, and scene-level subjects. Images were selected
+for clear, visually verifiable structures and use first- or third-person views
+according to the target capability.
+
+## Data Format
+
+```text
+datasuite/
+├── README.md
+├── gc/
+│   ├── data.json
+│   └── images/
+├── if/
+│   ├── data.json
+│   └── images/
+├── insight/
+│   ├── data.json
+│   └── images/
+└── outsight/
+    ├── data.json
+    └── images/
+```
+
+Each `data.json` is an array of evaluation cases. A case contains:
+
+- `task_id`, `source_task_id`, `category`, and `suite_split`;
+- `image_path`, `image_caption`, and `perspective` for the initial world;
+- `prompt` for the scene-grounded long-horizon objective;
+- `action`, `action_sequence`, and `action_sequence_steps` for the annotated
+  basic action reference;
+- `questions`, including the evaluation category, weight, question text, and
+  scoring notes;
+- dimension- or case-specific evaluation policies where applicable.
+
+## Download
+
+This folder is the complete local benchmark used by the companion code release.
+To obtain another copy from a future anonymous dataset host, download it into
+the code repository's `data/` directory:
+
+```bash
+hf download <anonymous-dataset-repository> \
+  --repo-type dataset \
+  --local-dir data
+```
+
+If access is restricted, request access on the dataset page and authenticate
+first with `hf auth login`.
+
+Individual configs can also be loaded with `datasets`:
+
+```python
+from datasets import load_dataset
+
+gc = load_dataset("<anonymous-dataset-repository>", "gc", split="train")
+interaction = load_dataset("<anonymous-dataset-repository>", "if", split="train")
+insight = load_dataset("<anonymous-dataset-repository>", "insight", split="train")
+outsight = load_dataset("<anonymous-dataset-repository>", "outsight", split="train")
+```
+
+Download the complete repository when running PlayWorld so that every relative
+`image_path` resolves from the same dataset root.
+
+## Use with PlayWorld
+
+Keep the code and dataset as separate directories:
+
+```text
+workspace/
+├── PlayWorld/       # code repository
+└── data/         # this dataset
+```
+
+Install the evaluation code from the sibling [`../code/`](../code/) directory, then point the Agent Player and
+Rubric Verifier to the selected `data.json` and its corresponding initial image.
+For example, the VQA evaluation entry point uses:
+
+```bash
+GEMINI_API_KEY="xxx" \
+DATASET="$PWD/data/gc/data.json" \
+TASK_ID=GC002 \
+VIDEO="$PWD/outputs/genie3/GC002/GC002_full_process.mp4" \
+REFERENCE_IMAGE="$PWD/data/gc/images/GC002.jpg" \
+OUTPUT="$PWD/evaluation/genie3/GC002_score.json" \
+./run_vqa_score.sh
+```
+
+See the code repository for Agent Player integration, world-model adapters, and
+the complete inference and evaluation protocol.
+
+## License
+
+Initial images originate from multiple sources, including Pexels and web image
+search results. Dataset users must follow the source-specific license and
+redistribution restrictions applicable to each asset. A single permissive
+license must not be assumed to cover every image.
+
+## Citation
+
+For double-blind review, cite the accompanying anonymous manuscript:
+
+```bibtex
+@article{playworld_anonymous,
+  title  = {PlayWorld: Benchmarking World Models with Agent Players over Long-Horizon Objectives},
+  author = {Anonymous Authors},
+  year   = {2026}
+}
+```