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README.md
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<!-- Provide a quick summary of the dataset. -->
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<p align="center">
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<img src="https://raw.githubusercontent.com/top-yun/SPARK/resources/problems.png" :height="300px" width="600px">
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</p>
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<p align="center">
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<img src="https://raw.githubusercontent.com/top-yun/SPARK/resources/examples.png" :height="400px" width="800px">
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</p>
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SPARK can reduce the fundamental multi-vision sensor information gap between images and multi-vision sensors. We generated 6,248 vision-language test samples automatically to investigate multi-vision sensory perception and multi-vision sensory reasoning on physical sensor knowledge proficiency across different formats, covering different types of sensor-related questions.
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<!-- Provide a quick summary of the dataset. -->
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<p align="center">
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<img src="https://raw.githubusercontent.com/top-yun/SPARK/main/resources/problems.png" :height="300px" width="600px">
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</p>
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<p align="center">
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<img src="https://raw.githubusercontent.com/top-yun/SPARK/main/resources/examples.png" :height="400px" width="800px">
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</p>
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SPARK can reduce the fundamental multi-vision sensor information gap between images and multi-vision sensors. We generated 6,248 vision-language test samples automatically to investigate multi-vision sensory perception and multi-vision sensory reasoning on physical sensor knowledge proficiency across different formats, covering different types of sensor-related questions.
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