Update README.md

README.md

@@ -19,13 +19,41 @@ dataset_info:
     dtype: string
   splits:
   - name: test
-    num_bytes: 1018562605.0
+    num_bytes: 1018562605
     num_examples: 10000
   download_size: 3713743593
-  dataset_size: 1018562605.0
+  dataset_size: 1018562605
 configs:
 - config_name: default
   data_files:
   - split: test
     path: data/test-*
+license: mit
+task_categories:
+- visual-question-answering
+tags:
+- finegrained-vqa
+- vqa
+- visual-reasoning
+pretty_name: FGVQA
+size_categories:
+- 10K<n<100K
 ---
+
+# FGVQA 
+This repository contains the FGVQA benchmark suite introduced in the paper [Same or Not? Enhancing Visual Perception in Vision-Language Models]().FGVQA contains 12,000 challenging (image, question, answer) tuples emphasizing fine-grained image understanding.
+
+The benchmark suite is composed of six sub-benchmarks: 
+1) [TWIN-eval](https://glab-caltech.github.io/twin/)
+2) [ILIAS](https://vrg.fel.cvut.cz/ilias/)
+3) [Google Landmarks v2](https://github.com/cvdfoundation/google-landmark)
+4) [MET](https://cmp.felk.cvut.cz/met/)
+5) [CUB](https://www.vision.caltech.edu/datasets/cub_200_2011/)
+6) [Inquire](https://inquire-benchmark.github.io/)
+
+## Citation 
+If you use the FGVQA benchmark suite in your research, please use the following BibTeX entry.
+```
+
+
+```