fixed typo

app.py

@@ -2,7 +2,7 @@ import os
 from pathlib import Path
 import time
 import gradio as gr
-from gadio.themes import Soft
+from gradio.themes import Soft
 import numpy as np
 import matplotlib.pyplot as plt
 from huggingface_hub import hf_hub_download
@@ -55,25 +55,23 @@ with gr.Blocks(title="UPLME", theme=Soft(primary_hue="blue")) as demo:
     gr.Markdown("# Empathy Prediction with Uncertainty Estimation")
     with gr.Row():
         with gr.Column():
-            essay_input = gr.Textbox(label="Response (E.g., Essay)", lines=10, placeholder="Enter the essay text here...")
+            essay_input = gr.Textbox(label="Response (E.g., Essay) towards the stimulus", lines=10, placeholder="Enter the essay text here...")
             article_input = gr.Textbox(label="Stimulus (E.g., News Article)", lines=10, placeholder="Enter the article text here...")
             button = gr.Button("Predict")
         with gr.Column():
-            output_mean = gr.Number(label="Predicted Empathy Score", precision=2)
+            output_mean = gr.Number(label="Predicted Empathy Score (0-100)", precision=2)
             ci_low = gr.Number(label="95% CI Lower Bound", precision=2)
             ci_upp = gr.Number(label="95% CI Upper Bound", precision=2)
         
-        fig = gr.Plot(label="Prediction +/- 95% CI")
+            fig = gr.Plot(label="Prediction +/- 95% CI")
 
         button.click(fn=predict_with_ci, inputs=[essay_input, article_input], outputs=[output_mean, ci_low, ci_upp, fig])
 
     gr.Markdown("## About")
     gr.Markdown("""
-    This application predicts empathy score using the UPLME model proposed in **UPLME: Uncertainty-Aware Probabilistic Language Modelling for Robust Empathy Regression** by **Md Rakibul Hasan, Md Zakir Hossain, Aneesh Krishna, Shafin Rahman and Tom Gedeon**.
-    The model provides both a mean empathy score and uncertainty estimates.
-    - **Response**: The text input representing the individual's response (e.g., essay).
-    - **Stimulus**: The text input representing the stimulus (e.g. newspaper article) that the response is based on.
-    - **Predicted Empathy**: The predicted empathy score on a scale from 0 to 100.
+    This application predicts empathy score and uncertainty estimates using the UPLME model proposed in **UPLME: Uncertainty-Aware Probabilistic Language Modelling for Robust Empathy Regression** by **Md Rakibul Hasan, Md Zakir Hossain, Aneesh Krishna, Shafin Rahman and Tom Gedeon**.
+    - Paper: https://arxiv.org/abs/2508.03520
+    - Code: https://github.com/hasan-rakibul/UPLME
     """)
 
 if __name__ == "__main__":