diff --git a/README.md b/README.md
index 667c7e1..8ae2f13 100644
--- a/README.md
+++ b/README.md
@@ -38,3 +38,17 @@ Some models require API keys which you can set as environment variables, e.g.
 ## Results
 
 Results are auto-saved to [mteb/arena-results](https://huggingface.co/datasets/mteb/arena-results).
+
+## Personal Leaderboards
+
+We have introduced a new feature that allows users to have their own personal leaderboards. This feature enables users to track their individual preferences and votes.
+
+### User Authentication
+
+To access your personal leaderboard, you need to log in using your Hugging Face account. The authentication is handled via OAuth.
+
+### Instructions
+
+1. Log in to your Hugging Face account.
+2. Navigate to the "Personal Leaderboard" tab in the UI.
+3. View your personal rankings based on your votes.
\ No newline at end of file
diff --git a/app.py b/app.py
index c310a2f..f8f967d 100644
--- a/app.py
+++ b/app.py
@@ -149,7 +149,15 @@ def load_elo_results(elo_results_dir):
                 with gr.Tab("🏆 Leaderboard", id=3):
                     build_leaderboard_tab(elo_results_file['sts'], leaderboard_table_file['sts'], task_type="STS")
 
+    with gr.Tab("🏅 Personal Leaderboard", id=13):
+        with gr.Tabs() as tabs_pl:
+            with gr.Tab("🔒 Login", id=14):
+                gr.Markdown("Please log in to view your personal leaderboard.")
+                gr.Button("Login with Hugging Face", variant="primary", elem_id="login_button")
+            with gr.Tab("🏆 Personal Leaderboard", id=15):
+                build_leaderboard_tab(elo_results_file['personal'], leaderboard_table_file['personal'], task_type="Personal")
+
     gr.Markdown(acknowledgment_md, elem_id="ack_markdown")
 
 block.queue(max_size=10)
-block.launch(share=True)
+block.launch(share=True)
\ No newline at end of file
diff --git a/leaderboard.py b/leaderboard.py
index 880a4ea..558df8d 100644
--- a/leaderboard.py
+++ b/leaderboard.py
@@ -11,6 +11,7 @@
     "Retrieval": "🔎",
     "Clustering": "✨",
     "STS": "☘️",
+    "Personal": "🏅",
 }
 
 def make_arena_leaderboard_md(elo_results):
@@ -137,6 +138,98 @@ def build_leaderboard_tab(elo_results_file, leaderboard_table_file, show_plot=Fa
 
     leader_component_values[:] = [md, p1, p2, p3, p4]
 
+    """
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown(
+                "#### Figure 1: Fraction of Model A Wins for All Non-tied A vs. B Battles"
+            )
+            plot_1 = gr.Plot(p1, show_label=False)
+        with gr.Column():
+            gr.Markdown(
+                "#### Figure 2: Battle Count for Each Combination of Models (without Ties)"
+            )
+            plot_2 = gr.Plot(p2, show_label=False)
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown(
+                "#### Figure 3: Bootstrap of Elo Estimates (1000 Rounds of Random Sampling)"
+            )
+            plot_3 = gr.Plot(p3, show_label=False)
+        with gr.Column():
+            gr.Markdown(
+                "#### Figure 4: Average Win Rate Against All Other Models (Assuming Uniform Sampling and No Ties)"
+            )
+            plot_4 = gr.Plot(p4, show_label=False)
+    """
+    # return [md_1, plot_1, plot_2, plot_3, plot_4]
+    return [md_1]
+
+def build_personal_leaderboard_tab(elo_results_file, leaderboard_table_file, user_id, show_plot=False, task_type="Personal"):
+    if elo_results_file is None:  # Do live update
+        md = "Loading ..."
+        p1 = p2 = p3 = p4 = None
+    else:
+        with open(elo_results_file, "rb") as fin:
+            elo_results = pickle.load(fin)
+
+        personal_elo_results = elo_results[user_id]
+        personal_arena_df = personal_elo_results["leaderboard_table_df"]
+        p1 = personal_elo_results["win_fraction_heatmap"]
+        p2 = personal_elo_results["battle_count_heatmap"]
+        p3 = personal_elo_results["bootstrap_elo_rating"]
+        p4 = personal_elo_results["average_win_rate_bar"]
+
+        md = f"""
+# 🏅 Personal Leaderboard: {task_type} {TASK_TYPE_TO_EMOJI[task_type]}
+"""
+    # | [GitHub](https://github.com/embeddings-benchmark) |
+    md_1 = gr.Markdown(md, elem_id="leaderboard_markdown")
+
+    if leaderboard_table_file:
+        model_table_df = load_leaderboard_table_csv(leaderboard_table_file)
+        personal_table_vals = get_arena_table(personal_arena_df, model_table_df, task_type=task_type)
+        md = make_arena_leaderboard_md(personal_elo_results)
+        gr.Markdown(md, elem_id="leaderboard_markdown")
+        gr.Dataframe(
+            headers=[
+                "Rank",
+                "🤖 Model",
+                "⭐ Personal Elo",
+                "📊 95% CI",
+                "🗳️ Votes",
+                "🥇 MTEB Overall Avg",
+                f"🥇 MTEB {task_type} Avg",                        
+                "Organization",
+                "License",
+            ],
+            datatype=[
+                "str",
+                "markdown",
+                "number",
+                "str",
+                "number",
+                "number", 
+                "number",
+                "str",
+                "str",
+            ],
+            value=personal_table_vals,
+            elem_id="personal_leaderboard_dataframe",
+            height=700,
+            column_widths=[50, 150, 100, 100, 100, 100, 100, 150, 150],
+            wrap=True,
+        )
+        if not show_plot:
+            gr.Markdown(
+                """## We are still collecting more votes on more models. The ranking will be updated very frequently. Please stay tuned!""",
+                elem_id="leaderboard_markdown",
+            )
+    else:
+        pass
+
+    leader_component_values[:] = [md, p1, p2, p3, p4]
+
     """
     with gr.Row():
         with gr.Column():