Update app.py

app.py

@@ -18,7 +18,8 @@ article = r"""
 📝 **Citation**
 <br>
 If our work is helpful for your research or applications, please cite us via:
-```bibtex
+```
+bibtex
 @article{toker2024diffusion,
   title={Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines},
   author={Toker, Michael and Orgad, Hadas and Ventura, Mor and Arad, Dana and Belinkov, Yonatan},
@@ -26,12 +27,27 @@ If our work is helpful for your research or applications, please cite us via:
   year={2024}
 }
 ```
+📧 **Abstact**
+<br>
+Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the image generation process. 
+However, the process by which the encoder produces the text representation is unknown. 
+We propose the Diffusion Lens, a method for analyzing the text encoder of T2I models by generating images from its intermediate representations. 
+Using the Diffusion Lens, we perform an extensive analysis of two recent T2I models. 
+Exploring compound prompts, we find that complex scenes describing multiple objects are composed progressively and more slowly compared to simple scenes; 
+Exploring knowledge retrieval, we find that representation of uncommon concepts requires further computation compared to common concepts, 
+and that knowledge retrieval is gradual across layers. 
+Overall, our findings provide valuable insights into the text encoder component in T2I pipelines.
+<br>
+```
 📧 **Contact**
 <br>
-If you have any questions, please feel free to open an issue or directly reach us out at <b>tok@cs.technuin.ac.il</b>.
+If you have any questions, please feel free to open an issue or directly reach us out at <b>tok@cs.technion.ac.il
+</b>.
 """
 
 
+
+
 model_num_of_layers = {
     'Stable Diffusion 1.4': 12,
     'Stable Diffusion 2.1': 22,