| ## 📘 Dataset Description |
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| **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). |
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| It covers three key capabilities: |
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| - **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. |
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| Each sample is also labeled with a visual perspective: |
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| - **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. |
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| This release includes **200 open-source samples** from the full dataset, provided for public research and benchmarking purposes. |
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| ## 📚 Citation |
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| If you use this dataset in your research, please cite it as follows: |
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| ```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} |
| } |
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