Datasets:

xiaojiahao
/

StaticEmbodiedBench

StaticEmbodiedBench is a dataset for evaluating vision-language models on embodied intelligence tasks, as featured in the OpenCompass leaderboard.

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.

📚 Citation

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

@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}
}