| title: WRBench | |
| emoji: 🎥 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: static | |
| pinned: false | |
| short_description: Persistent-state world model benchmark | |
| # WRBench | |
| WRBench is an open benchmark for camera-controlled video world models and | |
| diagnostic D1-D6 evaluation, introduced in *Current World Models Lack a | |
| Persistent State Core*. | |
| ## Start Here | |
| - Leaderboard: https://huggingface.co/spaces/WRBench/wrbench-leaderboard | |
| - Results dataset: https://huggingface.co/datasets/WRBench/wrbench-results | |
| - Benchmark videos: https://huggingface.co/datasets/WRBench/wrbench-videos | |
| - Natural-25 prompts and first frames: https://huggingface.co/datasets/WRBench/wrbench-natural25 | |
| - Human annotation labels: https://huggingface.co/datasets/WRBench/wrbench-human-annotations | |
| - Release collection: https://huggingface.co/collections/WRBench/wrbench-current-world-models-lack-a-persistent-state-core | |
| The paper reports a frozen benchmark table. The Hugging Face results dataset and | |
| leaderboard can be refreshed as new public results are released, so current | |
| model, video, and support counts should be read from the data files. | |
| ## Links | |
| - Paper: https://arxiv.org/abs/2606.20545 | |
| - Project page: https://jinplu.github.io/WRBench/ | |
| - Code: https://github.com/JinPLu/WRBench | |