Update src/streamlit_app.py

src/streamlit_app.py

@@ -4,6 +4,38 @@ import pandas as pd
 # ─── Page config ──────────────────────────────────────────────────────────────
 st.set_page_config(page_title="ExpertLongBench Leaderboard", layout="wide")
 
+
+logo_image = Image.open("./expertlongbench.png")
+
+# Display logo
+buffered = BytesIO()
+logo_image.save(buffered, format="PNG")
+img_data = base64.b64encode(buffered.getvalue()).decode("utf-8")
+
+st.markdown(
+    f"""
+    <div class="logo-container" style="display:flex; justify-content: center;">
+        <img src="data:image/png;base64,{img_data}" style="width:50%; max-width:700px;"/>
+    </div>
+    """,
+    unsafe_allow_html=True
+)
+
+st.markdown(
+    '''
+    <div class="header">
+        <br/>
+        <p style="font-size:22px;">
+        VERIFACT: Enhancing Long-Form Factuality Evaluation with Refined Fact Extraction and Reference Facts
+        </p>
+        <p style="font-size:20px;">
+            # 📑 <a href="">Paper</a> | 💻 <a href="">GitHub</a> | 🤗 <a href="">HuggingFace</a> 
+            ⚙️ <strong>Version</strong>: <strong>V1</strong> | <strong># Models</strong>: 12 | Updated: <strong>April 2025</strong>
+        </p>
+    </div>
+    ''',
+    unsafe_allow_html=True
+)
 # ─── Load data ────────────────────────────────────────────────────────────────
 @st.cache_data
 def load_data(path="src/models.json"):
@@ -25,7 +57,7 @@ max_ranks = {col: df[f"{col}_rank"].max() for col in score_cols}
 tab1, tab2 = st.tabs(["Leaderboard", "Benchmark Details"])
 
 with tab1:
-    st.markdown("**Leaderboard:** higher scores shaded green; best models bolded.")
+    # st.markdown("**Leaderboard:** higher scores shaded green; best models bolded.")
     # Build raw HTML table
     cols = ["Model"] + [f"T{i}" for i in range(1,12)] + ["Avg"]
     html = "<table style='border-collapse:collapse; width:100%; font-size:14px;'>"