| ## 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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| license: mit |
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