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@@ -26,7 +26,7 @@ We present SPHINX, a versatile multi-modal large language model (MLLM) with a mi
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  <img src="figs/pipeline1.png"/ width="100%"> <br>
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  </p>
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- On top of SPHINX, we propose to further mixvisual scales and sub-images for better capture fine-grained semantics on high-resolution images.
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  <p align="left">
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  <img src="figs/pipeline2.png"/ width="100%"> <br>
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  </p>
 
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  <img src="figs/pipeline1.png"/ width="100%"> <br>
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  </p>
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+ On top of SPHINX, we propose to further mix visual scales and sub-images for better capture fine-grained semantics on high-resolution images.
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  <p align="left">
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  <img src="figs/pipeline2.png"/ width="100%"> <br>
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  </p>