Merge branch 'main' of https://huggingface.co/spaces/double-ai/FormulaOne-Leaderboard

app.py

@@ -332,7 +332,7 @@ with blocks:
         with gr.TabItem("FormulaOne", id=0, elem_id="landing-accuracy-tab"):
 
             gr.HTML(
-                '<header class="text-center mb-12"><h1 class="text-4xl md:text-5xl font-bold text-gray-900 f1-h1">FormulaOne</h1></header>'
+                '<div align="center"><header class="text-center mb-12"><h1 class="text-4xl md:text-5xl font-bold text-gray-900 f1-h1" style="margin:0; display:inline;">FormulaOne</h1><span style="display:inline-block; margin-left:0.5em;"><h3 style="margin:0; display:inline;" class="text-4xl md:text-5xl font-bold text-gray-900 f1-h3 style=">by <a href="https://doubleai.com/">AAI</a></h3></header></div>'
             )
             with gr.Row(elem_id="landing-hero-row"):
                 with gr.Column(scale=7, elem_id="landing-hero-left"):
@@ -364,7 +364,7 @@ with blocks:
             # Pill-style selector aligned to the top-right
             with gr.Row(elem_id="f1-tier-select-row"):
                 tier_selector = gr.Radio(
-                    choices=list(TIER_TOTALS.keys()),
+                    choices=list(reversed(list(TIER_TOTALS.keys()))),
                     value="Deeper Tier",
                     label=None,
                     show_label=False,

src/about.py

@@ -3,11 +3,9 @@ PAPER_URL = "https://arxiv.org/abs/2507.13337"
 
 WHAT_IS_F1_HTML_TOP = f"""
 <div class="f1-container">
-  <header class="text-center mb-12">
-    <h1 class="text-4xl md:text-5xl font-bold text-gray-900 f1-h1">FormulaOne</h1>
-  </header>
-
+  <div align="center"><header class="text-center mb-12"><h1 class="text-4xl md:text-5xl font-bold text-gray-900 f1-h1" style="margin:0; display:inline;">FormulaOne</h1><span style="display:inline-block; margin-left:0.5em;"><h3 style="margin:0; display:inline;" class="text-4xl md:text-5xl font-bold text-gray-900 f1-h3 style=">by <a href="https://doubleai.com/">AAI</a></h3></header></div>
   <section>
+    <br/>
     <p class="text-lg mb-4 f1-p">Frontier AI models have recently demonstrated strong performance on mathematical and algorithmic benchmarks, including earning <a href="https://deepmind.google/discover/blog/advanced-version-of-gemini-with-deep-think-officially-achieves-gold-medal-standard-at-the-international-mathematical-olympiad/" target="_blank" rel="noopener noreferrer" class="f1-a">gold medals in olympiads</a>, and attaining <a href="https://arxiv.org/html/2502.06807v1" target="_blank" rel="noopener noreferrer" class="f1-a">top percentile ratings</a> in competitive programming contests. How well do such benchmarks capture the true depth of algorithmic reasoning, as it arises in real-world research problems?</p>
 
     <p class="text-lg mb-4 f1-p">We believe that existing benchmarks fail to capture the deep reasoning skills required for complex, research-level algorithmic problems. To address this gap, <a href="{PAPER_URL}" target="_blank" rel="noopener noreferrer" class="f1-a">we introduce <strong>FormulaOne</strong></a>.</p>