## 📘 Dataset Description

**StaticEmbodiedBench** is a dataset for evaluating vision-language models on embodied intelligence tasks, as featured in the [OpenCompass leaderboard](https://staging.opencompass.org.cn/embodied-intelligence/rank/brain).

It covers three key capabilities:

- **Macro Planning**: Decomposing a complex task into a sequence of simpler subtasks.
- **Micro Perception**: Performing concrete simple tasks such as spatial understanding and fine-grained perception.
- **Stage-wise Reasoning**: Deciding the next action based on the agent’s current state and perceptual inputs.

Each sample is also labeled with a visual perspective:

- **First-Person View**: The visual sensor is integrated with the agent, e.g., mounted on the end-effector.
- **Third-Person View**: The visual sensor is separate from the agent, e.g., top-down or observer view.

This release includes **200 open-source samples** from the full dataset, provided for public research and benchmarking purposes.

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## 📚 Citation

If you use this dataset in your research, please cite it as follows:

```bibtex
@misc{staticembodiedbench,
  title     = {StaticEmbodiedBench},
  author    = {Jiahao Xiao, Shengyu Guo, Chunyi Li, Bowen Yan and Jianbo Zhang},
  year      = {2025},
  url       = {https://huggingface.co/datasets/xiaojiahao/StaticEmbodiedBench}
}