Update README.md

README.md

@@ -4,22 +4,25 @@ pipeline_tag: text-to-image
 library_name: transformers
 ---
 
-# 🛡️DAA: Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models
+# Trigger without Trace: Towards Stealthy Backdoor Attack on Text-to-Image Diffusion Models
 
-This repository contains artifacts and code related to the paper: [**Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models**](https://huggingface.co/papers/2504.20518).
+This repository contains artifacts and code related to the paper: [**Trigger without Trace: Towards Stealthy Backdoor Attack on Text-to-Image Diffusion Models**]
 
-Code: https://github.com/Robin-WZQ/DAA
+Code: https://github.com/Robin-WZQ/TwT
 
-This study introduces a novel backdoor detection perspective from **Dynamic Attention Analysis (DAA)**, which shows that the **dynamic feature in attention maps** can serve as a much better indicator for backdoor detection in text-to-image diffusion models. By examining the dynamic evolution of cross-attention maps, backdoor samples exhibit distinct feature evolution patterns compared to benign samples, particularly at the `<EOS>` token.
+This study introduces TwT, an attack method based on syntactic structures that exhibits strong resistance to advanced detection methods.
 
 ## 📄 Citation
 
 If you find this project useful in your research, please consider cite:
 ```bibtex
-@article{wang2025dynamicattentionanalysisbackdoor,
-  title={Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models},
-  author={Zhongqi Wang and Jie Zhang and Shiguang Shan and Xilin Chen},
-  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
-  year={2025},
+@misc{zhang2025twt,
+      title={Trigger without Trace: Towards Stealthy Backdoor Attack on Text-to-Image Diffusion Models}, 
+      author={Jie Zhang and Zhongqi Wang and Shiguang Shan and Xilin Chen},
+      year={2025},
+      eprint={2503.17724},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2503.17724}, 
 }
 ```