Update app.py

app.py

@@ -114,7 +114,7 @@ with gr.Blocks() as iface:
     # 🧠 Predict Academic Impact of Newly Published Paper!
     ### Estimate the future academic impact of a paper using LLM
     ###### [Read the full paper](https://arxiv.org/abs/2408.03934)
-    ###### Please note that due to the characteristics of ZeroGPU, quantized models cannot be preloaded. Each time you click "Predict", the model will need to be reinitialized, which may take additional time （usually less than 20s）. 
+    ###### Please note that due to the characteristics of ZeroGPU, quantized models cannot be preloaded. Each time you click "Predict," the model will need to be reinitialized, which may take additional time （usually less than 20s）. 
     """)
     with gr.Row():
         with gr.Column():
@@ -132,14 +132,14 @@ with gr.Blocks() as iface:
             submit_button = gr.Button("Predict Impact", interactive=False)
         with gr.Column():
             output = gr.Label(label="Predicted Impact")
-                gr.Markdown("""
-                        **Important Notes**  
-                        - It is intended as a tool for research and educational purposes only.
-                        - Predicted impact is a probabilistic value generated by the model and does not reflect paper quality or novelty.  
-                        - The author takes no responsibility for the prediction results.
-                        - To identify potentially impactful papers, this study uses the sigmoid+MSE approach to optimize NDCG values (over sigmoid+BCE), resulting in predicted values concentrated between 0.1 and 0.9 due to the sigmoid gradient effect.
-                        - Generally, it is considered a predicted influence score greater than 0.65 to indicate an impactful paper.
-                        """)
+            gr.Markdown("""
+            **Important Notes**  
+            - It is intended as a tool for research and educational purposes only.
+            - Predicted impact is a probabilistic value generated by the model and does not reflect paper quality or novelty.  
+            - The author takes no responsibility for the prediction results.
+            - To identify potentially impactful papers, this study uses the sigmoid+MSE approach to optimize NDCG values (over sigmoid+BCE), resulting in predicted values concentrated between 0.1 and 0.9 due to the sigmoid gradient effect.
+            - Generally, it is considered a predicted influence score greater than 0.65 to indicate an impactful paper.
+            """)
 
     # 输入事件绑定
     title_input.change(
@@ -163,7 +163,6 @@ with gr.Blocks() as iface:
         examples=examples,
         inputs=[title_input, abstract_input],
         outputs=[validation_status, output],
-        cache_examples=True
+        cache_examples=False
     )
-
 iface.launch()