Update README.md

README.md

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 # What is it?
-W-Bench is the first holistic benchmark that incorporates four types of image editing techniques to assess the robustness of watermarking methods. Eleven representative watermarking methods are evaluated on the W-Bench. The W-Bench contains 10,000 images sourced from datasets such as COCO, Flickr, ShareGPT4V, etc.
+**W-Bench is the first benchmark to evaluate watermarking robustness across four image editing techniques.** 
+
+Eleven representative watermarking methods are evaluated on the W-Bench. The W-Bench contains 10,000 images sourced from datasets such as COCO, Flickr, ShareGPT4V, etc. 
+
+GitHub Page: [https://github.com/Shilin-LU/VINE](https://github.com/Shilin-LU/VINE)
 
 # Dataset Structure
 
-The evaluation set is divided into 6 different categories:
+The evaluation set consists of six subsets, each targeting a different type of AIGC-based image editing:
 - 1,000 samples for stochastic regeneration
 - 1,000 samples for deterministic regeneration
 - 1,000 samples for global editing