Add link to paper

This PR ensures the dataset is linked to (and can be found at) https://huggingface.co/papers/2503.18286. It also updates the license to Apache 2.0.

README.md

@@ -1,21 +1,22 @@
 ---
-license: mit
+language:
+- en
+license: apache-2.0
+size_categories:
+- 100K<n<1M
 task_categories:
 - image-classification
 - text-to-image
-language:
-- en
 tags:
 - Deepfake
 - AIGC
-size_categories:
-- 100K<n<1M
 ---
 
-
 [![GitHub](https://img.shields.io/badge/GitHub-Repo-blue?logo=github&logoColor=white)](https://github.com/Megum1/Co-Spy)
 
 # CO-SPY: Combining Semantic and Pixel Features to Detect Synthetic Images by AI (CVPR 2025)
+Paper: https://huggingface.co/papers/2503.18286
+
 With the rapid advancement of generative AI, it is now possible to synthesize high-quality images in a few seconds. Despite the power of these technologies, they raise significant concerns regarding misuse.
 To address this, various synthetic image detectors have been proposed. However, many of them struggle to generalize across diverse generation parameters and emerging generative models.
 In this repository, we introduce Co-Spy-Bench, a comprehensive benchmark designed to evaluate the robustness and effectiveness of synthetic image detectors under a wide range of generative conditions.