Update README.md

README.md

@@ -15,23 +15,31 @@ This dataset card is about the multi-subject personalization benchmark used in [
 
 ## Dataset Details
 
-- **Repository:** [More Information Needed]
-- **Paper[ICLR 2025]:** [More Information Needed]
-- **Model:** [More Information Needed]
+- **Repository:** https://github.com/MS-Diffusion/MS-Diffusion
+- **Paper[ICLR 2025]:** https://arxiv.org/pdf/2406.07209
+- **Model:** https://huggingface.co/doge1516/MS-Diffusion
 
 ## Dataset Structure
 
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
 
-[More Information Needed]
+This benchmark contains 7 categories, 40 subjects, and 13 combinations. Details of the data structure are defined in the paper and `msbench.py`.
 
 ## Dataset Source
 
+The subjects in MS-Bench are collected from [DreamBench](https://github.com/google/dreambooth), [CustomConcept101](https://github.com/adobe-research/custom-diffusion/tree/main/customconcept101), and the Internet. **This benchmark is for research use only.**
 
 ## Citation
 
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 
-**BibTeX:**
-
-[More Information Needed]
+```bibtex
+@inproceedings{
+  wang2025msdiffusion,
+  title={{MS}-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance},
+  author={Xierui Wang and Siming Fu and Qihan Huang and Wanggui He and Hao Jiang},
+  booktitle={The Thirteenth International Conference on Learning Representations},
+  year={2025},
+  url={https://openreview.net/forum?id=PJqP0wyQek}
+}
+```