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# SPARK (multi-vision Sensor Perception And Reasoning benchmarK)
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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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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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## Dataset Details
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## Uses
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# SPARK (multi-vision Sensor Perception And Reasoning benchmarK)
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[**github**](https://github.com/top-yun/SPARK)[**🤗 Dataset**](https://huggingface.co/datasets/topyun/SPARK)
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## Dataset Details
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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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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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## Uses
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