Update README.md

README.md

@@ -58,7 +58,7 @@ size_categories:
 - **Paper:** [Prompt Stealing Attacks Against Text-to-Image Generation Models](https://arxiv.org/abs/2302.09923)
 - **Point of Contact:** [Xinyue Shen]([email protected])
 
-### Dataset Summary
+### LexicaDataset
 
 LexicaDataset is a large-scale text-to-image prompt dataset shared in [[USENIX'24] Prompt Stealing Attacks Against Text-to-Image Generation Models](https://arxiv.org/abs/2302.09923).
 It contains **61,467 prompt-image pairs** collected from [Lexica](https://lexica.art/).
@@ -69,9 +69,7 @@ Data collection details can be found in the paper.
 
 We randomly sample 80% of a dataset as the training dataset and the rest 20% as the testing dataset.
 
-
-### Loading LexicaDataset
-
+### Load LexicaDataset
 
 You can use the Hugging Face [`Datasets`](https://huggingface.co/docs/datasets/quickstart) library to easily load prompts and images from LexicaDataset.
 
@@ -103,19 +101,17 @@ testset  = load_dataset('vera365/lexica_dataset', split='test')
 | `modifier10`        | `sequence` | Modifiers in the prompt that appear more than 10 times in the whole dataset. We regard them as labels to train the modifier detector |
 | `modifier10_vector` | `sequence` | One-hot vector of `modifier10`                               |
 
-
 ## Ethics & Disclosure
 
 According to the [terms and conditions of Lexica](https://lexica.art/terms), images on the website are available under the Creative Commons Noncommercial 4.0 Attribution International License. We strictly followed Lexica’s Terms and Conditions, utilized only the official Lexica API for data retrieval, and disclosed our research to Lexica. We also responsibly disclosed our findings to related prompt marketplaces.
 
-## Licensing
+## License
 
 The LexicaDataset dataset is available under the [CC-BY 4.0 License](https://creativecommons.org/licenses/by/4.0/).
 
 ## Citation
 
 If you find this useful in your research, please consider citing:
-
 ```bibtex
 @inproceedings{SQBZ24,
   author = {Xinyue Shen and Yiting Qu and Michael Backes and Yang Zhang},