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README.md

@@ -47,7 +47,7 @@ configs:
 
 ### Dataset Summary
 
-PittImageVideoAdsDataset is the image and video advertisement dataset released with *Automatic Understanding of Image and Video Advertisements*. It contains 64,832 image advertisements and 3,477 YouTube advertisement videos, with human annotations for topics, sentiments, slogans, persuasive strategies, symbolic references, and action/reason Q/A.
+PittImageVideoAdsDataset is the image and video advertisement dataset released with *Automatic Understanding of Image and Video Advertisements*. The paper reports 64,832 image advertisements and 3,477 YouTube advertisement videos, with human annotations for topics, sentiments, slogans, persuasive strategies, symbolic references, and action/reason Q/A. This Hugging Face version exposes the public annotation rows that can be reconstructed from the official released files.
 
 This loader exposes two configurations:
 
@@ -131,14 +131,21 @@ The annotation text and Q/A responses are in English (`en`).
 
 ### Data Splits
 
-Both configurations expose one `train` split because the upstream release is an annotation corpus and does not define train, validation, or test partitions.
+Both configurations expose one `train` split because the upstream release is an annotation corpus and does not define train, validation, or test partitions. The `train` name is a Hugging Face packaging convention here; it is not an official training partition from the paper.
 
 | Config | Split | Rows |
 | --- | --- | ---: |
 | `image_ads` | train | 64,454 annotated image paths |
 | `video_ads` | train | 3,477 videos |
 
-The original image dataset contains 64,832 images. This loader emits the union of image paths found in the public annotation JSON files.
+The row counts line up with the public files as follows:
+
+| Source count | Images | Videos |
+| --- | ---: | ---: |
+| Paper-reported dataset size | 64,832 | 3,477 |
+| Rows emitted by this loader | 64,454 | 3,477 |
+
+The image count is lower than the paper-reported total because this loader emits the union of image paths found in the public annotation JSON files. The remaining paper-reported images are not present as annotated rows in those JSON files, so the loader does not synthesize empty examples for them.
 
 ## Dataset Creation