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README.md

@@ -24,6 +24,20 @@ The ability to distinguish subtle differences between visually similar images is
 
 VLM-SubtleBench is a benchmark designed to evaluate VLMs on **subtle comparative reasoning** — detecting fine-grained differences between highly similar image pairs that are easy for humans but challenging for state-of-the-art VLMs. Unlike prior benchmarks restricted to natural image datasets, VLM-SubtleBench spans diverse domains including industrial, aerial, and medical imagery.
 
+## Benchmark Summary
+
+| | |
+|---|---|
+| **Total QA pairs** | 12,923 |
+| **Difference types** | 10 |
+| **Image domains** | 6 (Natural, Industrial, Aerial, Synthetic, Medical) |
+| **Data sources** | 14 |
+| **Human captions** | 1,200 |
+| **Splits** | test (11,688) / val (1,235) |
+| **Task format** | Multiple-choice VQA + Image Difference Captioning |
+
+> **Note**: Medical domain images (MIMIC-CXR, 362 pairs) are not included due to licensing restrictions, but their QA entries are included in `qa.json`. See [Medical Data](#medical-data-mimic-cxr) below for instructions on how to obtain the images.
+
 ## Medical Data (MIMIC-CXR)
 
 The medical domain QA entries (362 attribute comparison pairs from MIMIC-CXR chest X-rays) are included in `qa.json`, but the corresponding images are not included due to [PhysioNet licensing requirements](https://physionet.org/content/mimic-cxr-jpg/2.1.0/).