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@@ -82,6 +82,7 @@ Each entry contains **a question ID, a question, provenance documents, a ground
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  The dataset contains **a collection of images** stored under the directory:
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  ```
 
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  IMAGE/images/
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  ```
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@@ -128,9 +129,9 @@ To evaluate the retrieval performance, we consider the following metrics:
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  - **Visual Recall** measures the percentage of retrieved images relative to the total number of images in the ground truth.
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  It is computed as:
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- $$
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  \text{Visual Recall} = \frac{\text{Retrieved Relevant Images}}{\text{Total Relevant Images in Ground Truth}}
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- $$
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  where "Retrieved Relevant Images" refers to the number of images retrieved that are present in the ground truth, and "Total Relevant Images in Ground Truth" refers to the total number of relevant images that should have been retrieved.
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  The dataset contains **a collection of images** stored under the directory:
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  ```
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+
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  IMAGE/images/
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  ```
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  - **Visual Recall** measures the percentage of retrieved images relative to the total number of images in the ground truth.
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  It is computed as:
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+ ![$$
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  \text{Visual Recall} = \frac{\text{Retrieved Relevant Images}}{\text{Total Relevant Images in Ground Truth}}
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+ $$](https://huggingface.co/datasets/MRAMG/MRAMG-Bench/blob/main/cced8a3bb54ebd5906287f110a1e225.png)
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  where "Retrieved Relevant Images" refers to the number of images retrieved that are present in the ground truth, and "Total Relevant Images in Ground Truth" refers to the total number of relevant images that should have been retrieved.
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