Adopt ten-component benchmark protocol

blobs/columns.md

@@ -0,0 +1,16 @@
+## Column guide
+
+- **Overall-10** — Prompt-macro average across the ten applicable components, scaled from 0–3 to 0–100.
+- **Checklist** — Satisfaction of prompt-specific verification checklist items.
+- **Rubric Adaptive** — Satisfaction of prompt-specific weighted evaluation-rubric criteria.
+- **Prompt Faithfulness** — How completely the image follows the user prompt.
+- **Image Quality** — Visual fidelity, clarity, detail, and absence of rendering defects.
+- **Text Rendering** — Correctness and legibility of text shown in the image.
+- **AI Naturalness** — How natural and non-synthetic the image appears.
+- **Composition & Aesthetics** — Layout, balance, coherence, and aesthetic quality.
+- **Physical Plausibility** — Consistency with real-world geometry, anatomy, lighting, and physics.
+- **Visual Reference** — Consistency with required visual-reference entities or attributes.
+- **Text Reference** — Factual consistency with required text-derived knowledge.
+- **Coverage** — Percentage and count of prompts with valid scored results. Missing-result handling follows the model-specific policy described in Metric Details.
+
+All score columns use the 0–100 public scale. **N/A** means a component is not applicable, not a score of zero.

blobs/intro.md

@@ -1,5 +1,7 @@
-**SearchGen-Bench** evaluates image generators on 751 prompts spanning 22 domains and 12 failure modes. It separates prompts that generators can answer without retrieval from visually and textually search-intensive prompts.
+## Where visual generators know—and where they need search
 
-The primary leaderboard metric, **Overall-9**, is the prompt-macro average of nine physical-plausibility judge components. The paper-compatible **Overall-10** additionally includes Text Reference. Use the scoreboard selector to inspect component, domain, and failure-mode rankings.
+**SearchGen-Bench** compares image generators across 751 evaluation prompts, knowledge-boundary strata, 22 domains, and 12 recurring failure modes. The benchmark separates 100 **NoSearch** prompts that strong generators can answer from parametric knowledge from 651 **SearchIntensive** prompts whose visual or textual requirements expose gaps that retrieval can address.
+
+The primary metric is **Overall-10**: a prompt-macro average over the canonical ten applicable FF-judge+PP components, reported on a 0–100 scale. Use the scoreboard selector to inspect results by component, domain, or failure mode.
 
 All scores are generated from versioned prompt-level records. Counts and coverage are shown because domains and failure modes are multi-label and some commercial generators have incomplete evaluations.

blobs/metrics.md

@@ -1,8 +1,6 @@
 ## Metric details
 
-**Overall-9** is the mean of all applicable public components for each prompt, followed by a macro average over prompts and conversion from the raw 0–3 scale to 0–100. Its components are Checklist, Rubric Adaptive, Prompt Faithfulness, Image Quality, Text Rendering, AI Naturalness, Composition and Aesthetics, Physical Plausibility, and Visual Reference.
-
-**Overall-10 (Paper)** uses the same procedure but additionally includes Text Reference. It is retained so results can be reconciled with the paper's canonical tables.
+**Overall-10** is the primary benchmark metric. For each prompt, it averages all applicable values across Checklist, Rubric Adaptive, Prompt Faithfulness, Image Quality, Text Rendering, AI Naturalness, Composition and Aesthetics, Physical Plausibility, Visual Reference, and Text Reference. Prompt-level means are then macro-averaged and converted from the raw 0–3 scale to 0–100.
 
 An inapplicable component is excluded from its prompt-level mean. Missing model results are zero-filled by default, matching the canonical paper convention. Missing Grok-Imagine-Image and Qwen-Image-2-Pro results are excluded from their denominators. Coverage always reports valid scored prompts over prompts in the selected group.
 

data/leaderboard_by_failure_mode.json

@@ -9,6 +9,7 @@
         "physical_plausibility": 415,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 336,
         "text_rendering": 376,
         "visual_reference_evaluation": 439
       },
@@ -20,6 +21,7 @@
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         "prompt_faithfulness": 68.5,
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@@ -43,6 +45,7 @@
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data/leaderboard_by_stratum.json

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         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 263,
         "text_rendering": 254,
         "visual_reference_evaluation": 172
       },
@@ -1658,6 +1755,7 @@
         "physical_plausibility": 48.7,
         "prompt_faithfulness": 12.4,
         "rubric_adaptive": 16.2,
+        "text_reference_evaluation": 3.6,
         "text_rendering": 3.9,
         "visual_reference_evaluation": 9.9
       },
@@ -1681,6 +1779,7 @@
         "physical_plausibility": 201,
         "prompt_faithfulness": 263,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 262,
         "text_rendering": 249,
         "visual_reference_evaluation": 171
       },
@@ -1692,6 +1791,7 @@
         "physical_plausibility": 44.6,
         "prompt_faithfulness": 9.1,
         "rubric_adaptive": 13.6,
+        "text_reference_evaluation": 1.7,
         "text_rendering": 2.8,
         "visual_reference_evaluation": 7.2
       },
@@ -1715,6 +1815,7 @@
         "physical_plausibility": 203,
         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 264,
         "text_rendering": 244,
         "visual_reference_evaluation": 172
       },
@@ -1726,6 +1827,7 @@
         "physical_plausibility": 37.8,
         "prompt_faithfulness": 9.9,
         "rubric_adaptive": 12.4,
+        "text_reference_evaluation": 1.1,
         "text_rendering": 1.6,
         "visual_reference_evaluation": 9.3
       },
@@ -1749,6 +1851,7 @@
         "physical_plausibility": 216,
         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 264,
         "text_rendering": 249,
         "visual_reference_evaluation": 239
       },
@@ -1760,6 +1863,7 @@
         "physical_plausibility": 8.1,
         "prompt_faithfulness": 0.6,
         "rubric_adaptive": 1.7,
+        "text_reference_evaluation": 0.2,
         "text_rendering": 0.0,
         "visual_reference_evaluation": 0.1
       },
@@ -1785,6 +1889,7 @@
         "physical_plausibility": 305,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 194,
         "text_rendering": 260,
         "visual_reference_evaluation": 333
       },
@@ -1796,6 +1901,7 @@
         "physical_plausibility": 71.2,
         "prompt_faithfulness": 69.2,
         "rubric_adaptive": 71.7,
+        "text_reference_evaluation": 63.7,
         "text_rendering": 81.5,
         "visual_reference_evaluation": 65.7
       },
@@ -1819,6 +1925,7 @@
         "physical_plausibility": 319,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 190,
         "text_rendering": 223,
         "visual_reference_evaluation": 333
       },
@@ -1830,6 +1937,7 @@
         "physical_plausibility": 73.3,
         "prompt_faithfulness": 61.1,
         "rubric_adaptive": 65.4,
+        "text_reference_evaluation": 55.6,
         "text_rendering": 70.8,
         "visual_reference_evaluation": 60.4
       },
@@ -1853,6 +1961,7 @@
         "physical_plausibility": 278,
         "prompt_faithfulness": 356,
         "rubric_adaptive": 356,
+        "text_reference_evaluation": 194,
         "text_rendering": 236,
         "visual_reference_evaluation": 321
       },
@@ -1864,6 +1973,7 @@
         "physical_plausibility": 66.5,
         "prompt_faithfulness": 60.8,
         "rubric_adaptive": 64.9,
+        "text_reference_evaluation": 54.6,
         "text_rendering": 69.0,
         "visual_reference_evaluation": 60.2
       },
@@ -1887,6 +1997,7 @@
         "physical_plausibility": 293,
         "prompt_faithfulness": 378,
         "rubric_adaptive": 378,
+        "text_reference_evaluation": 178,
         "text_rendering": 196,
         "visual_reference_evaluation": 343
       },
@@ -1898,6 +2009,7 @@
         "physical_plausibility": 65.8,
         "prompt_faithfulness": 47.9,
         "rubric_adaptive": 54.1,
+        "text_reference_evaluation": 41.9,
         "text_rendering": 66.0,
         "visual_reference_evaluation": 47.2
       },
@@ -1921,6 +2033,7 @@
         "physical_plausibility": 308,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 200,
         "text_rendering": 200,
         "visual_reference_evaluation": 353
       },
@@ -1932,6 +2045,7 @@
         "physical_plausibility": 60.3,
         "prompt_faithfulness": 44.0,
         "rubric_adaptive": 50.2,
+        "text_reference_evaluation": 39.9,
         "text_rendering": 62.0,
         "visual_reference_evaluation": 43.2
       },
@@ -1955,6 +2069,7 @@
         "physical_plausibility": 308,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 194,
         "text_rendering": 225,
         "visual_reference_evaluation": 351
       },
@@ -1966,6 +2081,7 @@
         "physical_plausibility": 58.3,
         "prompt_faithfulness": 44.8,
         "rubric_adaptive": 50.3,
+        "text_reference_evaluation": 33.2,
         "text_rendering": 54.4,
         "visual_reference_evaluation": 41.9
       },
@@ -1989,6 +2105,7 @@
         "physical_plausibility": 312,
         "prompt_faithfulness": 386,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 203,
         "text_rendering": 203,
         "visual_reference_evaluation": 332
       },
@@ -2000,6 +2117,7 @@
         "physical_plausibility": 58.8,
         "prompt_faithfulness": 41.9,
         "rubric_adaptive": 48.3,
+        "text_reference_evaluation": 28.5,
         "text_rendering": 43.2,
         "visual_reference_evaluation": 40.8
       },
@@ -2023,6 +2141,7 @@
         "physical_plausibility": 314,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 221,
         "text_rendering": 214,
         "visual_reference_evaluation": 333
       },
@@ -2034,6 +2153,7 @@
         "physical_plausibility": 59.5,
         "prompt_faithfulness": 38.4,
         "rubric_adaptive": 45.0,
+        "text_reference_evaluation": 23.0,
         "text_rendering": 35.0,
         "visual_reference_evaluation": 37.4
       },
@@ -2057,6 +2177,7 @@
         "physical_plausibility": 350,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 214,
         "text_rendering": 199,
         "visual_reference_evaluation": 331
       },
@@ -2068,6 +2189,7 @@
         "physical_plausibility": 44.8,
         "prompt_faithfulness": 21.9,
         "rubric_adaptive": 29.0,
+        "text_reference_evaluation": 6.9,
         "text_rendering": 12.8,
         "visual_reference_evaluation": 21.6
       },
@@ -2091,6 +2213,7 @@
         "physical_plausibility": 305,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 231,
         "text_rendering": 222,
         "visual_reference_evaluation": 332
       },
@@ -2102,6 +2225,7 @@
         "physical_plausibility": 48.5,
         "prompt_faithfulness": 20.4,
         "rubric_adaptive": 27.7,
+        "text_reference_evaluation": 7.2,
         "text_rendering": 11.0,
         "visual_reference_evaluation": 20.6
       },
@@ -2125,6 +2249,7 @@
         "physical_plausibility": 301,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 235,
         "text_rendering": 210,
         "visual_reference_evaluation": 331
       },
@@ -2136,6 +2261,7 @@
         "physical_plausibility": 47.3,
         "prompt_faithfulness": 14.7,
         "rubric_adaptive": 21.7,
+        "text_reference_evaluation": 3.0,
         "text_rendering": 6.0,
         "visual_reference_evaluation": 14.3
       },
@@ -2159,6 +2285,7 @@
         "physical_plausibility": 333,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 215,
         "text_rendering": 192,
         "visual_reference_evaluation": 331
       },
@@ -2170,6 +2297,7 @@
         "physical_plausibility": 36.2,
         "prompt_faithfulness": 15.5,
         "rubric_adaptive": 21.2,
+        "text_reference_evaluation": 2.9,
         "text_rendering": 3.6,
         "visual_reference_evaluation": 15.7
       },
@@ -2193,6 +2321,7 @@
         "physical_plausibility": 340,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 266,
         "text_rendering": 247,
         "visual_reference_evaluation": 349
       },
@@ -2204,6 +2333,7 @@
         "physical_plausibility": 33.5,
         "prompt_faithfulness": 11.2,
         "rubric_adaptive": 15.7,
+        "text_reference_evaluation": 2.6,
         "text_rendering": 2.8,
         "visual_reference_evaluation": 11.7
       },

data/leaderboard_overall.json

@@ -8,6 +8,7 @@
       "physical_plausibility": 558,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 486,
       "text_rendering": 544,
       "visual_reference_evaluation": 599
     },
@@ -19,6 +20,7 @@
       "physical_plausibility": 76.7,
       "prompt_faithfulness": 69.4,
       "rubric_adaptive": 70.8,
+      "text_reference_evaluation": 54.6,
       "text_rendering": 75.4,
       "visual_reference_evaluation": 65.7
     },
@@ -42,6 +44,7 @@
       "physical_plausibility": 627,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 480,
       "text_rendering": 500,
       "visual_reference_evaluation": 598
     },
@@ -53,6 +56,7 @@
       "physical_plausibility": 78.4,
       "prompt_faithfulness": 62.3,
       "rubric_adaptive": 65.1,
+      "text_reference_evaluation": 47.4,
       "text_rendering": 66.3,
       "visual_reference_evaluation": 59.8
     },
@@ -76,6 +80,7 @@
       "physical_plausibility": 539,
       "prompt_faithfulness": 717,
       "rubric_adaptive": 717,
+      "text_reference_evaluation": 487,
       "text_rendering": 517,
       "visual_reference_evaluation": 582
     },
@@ -87,6 +92,7 @@
       "physical_plausibility": 73.1,
       "prompt_faithfulness": 62.0,
       "rubric_adaptive": 64.1,
+      "text_reference_evaluation": 46.0,
       "text_rendering": 63.4,
       "visual_reference_evaluation": 58.9
     },
@@ -110,6 +116,7 @@
       "physical_plausibility": 544,
       "prompt_faithfulness": 742,
       "rubric_adaptive": 742,
+      "text_reference_evaluation": 473,
       "text_rendering": 471,
       "visual_reference_evaluation": 606
     },
@@ -121,6 +128,7 @@
       "physical_plausibility": 71.7,
       "prompt_faithfulness": 50.0,
       "rubric_adaptive": 54.2,
+      "text_reference_evaluation": 35.7,
       "text_rendering": 56.7,
       "visual_reference_evaluation": 46.2
     },
@@ -144,6 +152,7 @@
       "physical_plausibility": 561,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 492,
       "text_rendering": 467,
       "visual_reference_evaluation": 617
     },
@@ -155,6 +164,7 @@
       "physical_plausibility": 67.9,
       "prompt_faithfulness": 47.3,
       "rubric_adaptive": 51.9,
+      "text_reference_evaluation": 33.1,
       "text_rendering": 54.0,
       "visual_reference_evaluation": 43.2
     },
@@ -178,6 +188,7 @@
       "physical_plausibility": 593,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 486,
       "text_rendering": 518,
       "visual_reference_evaluation": 615
     },
@@ -189,6 +200,7 @@
       "physical_plausibility": 64.0,
       "prompt_faithfulness": 45.9,
       "rubric_adaptive": 50.2,
+      "text_reference_evaluation": 28.2,
       "text_rendering": 48.9,
       "visual_reference_evaluation": 39.9
     },
@@ -212,6 +224,7 @@
       "physical_plausibility": 604,
       "prompt_faithfulness": 750,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 501,
       "text_rendering": 483,
       "visual_reference_evaluation": 596
     },
@@ -223,6 +236,7 @@
       "physical_plausibility": 65.6,
       "prompt_faithfulness": 41.6,
       "rubric_adaptive": 47.2,
+      "text_reference_evaluation": 23.4,
       "text_rendering": 38.1,
       "visual_reference_evaluation": 38.4
     },
@@ -246,6 +260,7 @@
       "physical_plausibility": 594,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 522,
       "text_rendering": 498,
       "visual_reference_evaluation": 597
     },
@@ -257,6 +272,7 @@
       "physical_plausibility": 66.0,
       "prompt_faithfulness": 39.1,
       "rubric_adaptive": 44.0,
+      "text_reference_evaluation": 17.8,
       "text_rendering": 28.9,
       "visual_reference_evaluation": 36.4
     },
@@ -280,6 +296,7 @@
       "physical_plausibility": 676,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 516,
       "text_rendering": 475,
       "visual_reference_evaluation": 595
     },
@@ -291,6 +308,7 @@
       "physical_plausibility": 48.6,
       "prompt_faithfulness": 24.5,
       "rubric_adaptive": 30.5,
+      "text_reference_evaluation": 7.7,
       "text_rendering": 11.3,
       "visual_reference_evaluation": 23.8
     },
@@ -314,6 +332,7 @@
       "physical_plausibility": 599,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 536,
       "text_rendering": 501,
       "visual_reference_evaluation": 596
     },
@@ -325,6 +344,7 @@
       "physical_plausibility": 51.5,
       "prompt_faithfulness": 21.7,
       "rubric_adaptive": 27.9,
+      "text_reference_evaluation": 6.6,
       "text_rendering": 8.4,
       "visual_reference_evaluation": 21.1
     },
@@ -348,6 +368,7 @@
       "physical_plausibility": 597,
       "prompt_faithfulness": 750,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 537,
       "text_rendering": 483,
       "visual_reference_evaluation": 594
     },
@@ -359,6 +380,7 @@
       "physical_plausibility": 49.0,
       "prompt_faithfulness": 16.0,
       "rubric_adaptive": 22.9,
+      "text_reference_evaluation": 3.6,
       "text_rendering": 4.7,
       "visual_reference_evaluation": 15.1
     },
@@ -382,6 +404,7 @@
       "physical_plausibility": 631,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 521,
       "text_rendering": 465,
       "visual_reference_evaluation": 595
     },
@@ -393,6 +416,7 @@
       "physical_plausibility": 40.4,
       "prompt_faithfulness": 16.7,
       "rubric_adaptive": 21.8,
+      "text_reference_evaluation": 3.5,
       "text_rendering": 3.5,
       "visual_reference_evaluation": 16.8
     },
@@ -416,6 +440,7 @@
       "physical_plausibility": 656,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 630,
       "text_rendering": 596,
       "visual_reference_evaluation": 688
     },
@@ -427,6 +452,7 @@
       "physical_plausibility": 20.0,
       "prompt_faithfulness": 6.0,
       "rubric_adaptive": 8.7,
+      "text_reference_evaluation": 1.2,
       "text_rendering": 1.2,
       "visual_reference_evaluation": 6.0
     },

data/manifest.json

@@ -88,7 +88,6 @@
   },
   "schema_version": "1.0.0",
   "scoring": {
-    "excluded_public_component": "text_reference_evaluation",
     "missing_policy_default": "zero_fill",
     "missing_policy_exceptions": [
       "qwen_image_2_pro",
@@ -117,6 +116,8 @@
       "physical_plausibility",
       "visual_reference_evaluation"
     ],
+    "overall_9_excluded_component": "text_reference_evaluation",
+    "primary_metric": "overall_10",
     "public_rounding_decimals": 1,
     "scale_public": [
       0,

index.html

@@ -24,6 +24,12 @@
   <header>
     <h1>SearchGen-Bench</h1>
     <p class="subtitle">Evaluating search-grounded image generation across knowledge boundaries</p>
+    <div class="stat-grid" aria-label="Benchmark summary">
+      <article><strong>751</strong><span>evaluation prompts</span></article>
+      <article><strong>22</strong><span>knowledge domains</span></article>
+      <article><strong>12</strong><span>failure modes</span></article>
+      <article><strong>10</strong><span>score components</span></article>
+    </div>
     <div id="intro-container" class="intro-container">
       <div id="intro-markdown" class="markdown-body"></div>
     </div>
@@ -32,6 +38,9 @@
       <button class="expand-btn" data-target="metrics-details">
         <i class="fa-solid fa-chart-line"></i> Metric Details
       </button>
+      <button class="expand-btn" data-target="column-guide">
+        <i class="fa-solid fa-table-columns"></i> Column Guide
+      </button>
       <button class="expand-btn" data-target="submit-here">
         <i class="fa-solid fa-rocket"></i> Submit Here
       </button>
@@ -50,6 +59,7 @@
     </div>
 
     <div id="metrics-details" class="expandable-content markdown-body"></div>
+    <div id="column-guide" class="expandable-content markdown-body"></div>
     <div id="submit-here" class="expandable-content markdown-body"></div>
   </header>
 
@@ -104,6 +114,7 @@
         </table>
       </div>
     </div>
+    <p class="table-note">Click any column heading to sort. Hover over a heading for a short definition, or open the Column Guide above for the complete explanation.</p>
 
     <!-- Citation Section -->
     <section id="citation-section" class="citation-section">

main.js

@@ -9,17 +9,19 @@ const TOP_SCROLLBAR_WRAPPER = document.getElementById('top-scrollbar-wrapper');
 const TOP_SCROLLBAR_CONTENT = document.getElementById('top-scrollbar-content');
 const BOTTOM_SCROLLBAR_WRAPPER = document.getElementById('bottom-scrollbar-wrapper');
 const TABLE = document.getElementById('leaderboard-table');
+const EXCLUDED_MODELS = new Set(['imagen3fast']);
 
 const COMPONENTS = [
-  ['checklist', 'Checklist'],
-  ['rubric_adaptive', 'Rubric Adaptive'],
-  ['prompt_faithfulness', 'Prompt Faithfulness'],
-  ['image_quality', 'Image Quality'],
-  ['text_rendering', 'Text Rendering'],
-  ['ai_naturalness', 'AI Naturalness'],
-  ['composition_and_aesthetics', 'Composition & Aesthetics'],
-  ['physical_plausibility', 'Physical Plausibility'],
-  ['visual_reference_evaluation', 'Visual Reference'],
+  ['checklist', 'Checklist', 'Satisfaction of prompt-specific verification checklist items.'],
+  ['rubric_adaptive', 'Rubric Adaptive', 'Satisfaction of prompt-specific weighted evaluation-rubric criteria.'],
+  ['prompt_faithfulness', 'Prompt Faithfulness', 'How completely the image follows the user prompt.'],
+  ['image_quality', 'Image Quality', 'Visual fidelity, clarity, detail, and absence of rendering defects.'],
+  ['text_rendering', 'Text Rendering', 'Correctness and legibility of text shown in the image.'],
+  ['ai_naturalness', 'AI Naturalness', 'How natural and non-synthetic the image appears.'],
+  ['composition_and_aesthetics', 'Composition & Aesthetics', 'Layout, balance, coherence, and aesthetic quality.'],
+  ['physical_plausibility', 'Physical Plausibility', 'Consistency with real-world geometry, anatomy, lighting, and physics.'],
+  ['visual_reference_evaluation', 'Visual Reference', 'Consistency with required visual-reference entities or attributes.'],
+  ['text_reference_evaluation', 'Text Reference', 'Factual consistency with required text-derived knowledge.'],
 ];
 
 let manifest = null;
@@ -27,7 +29,7 @@ let strataData = {};
 let domainData = {};
 let failureModeData = {};
 let displayRows = [];
-let sortKey = 'overall_9';
+let sortKey = 'overall_10';
 let sortAsc = false;
 
 const escapeHtml = (value) => String(value ?? '')
@@ -59,12 +61,12 @@ async function init() {
     SEARCH_INPUT.addEventListener('input', updateBoard);
     BOARD_SELECT.addEventListener('change', () => {
       STRATUM_CONTROL.hidden = BOARD_SELECT.value !== 'components';
-      sortKey = BOARD_SELECT.value === 'components' ? 'overall_9' : 'All';
+      sortKey = BOARD_SELECT.value === 'components' ? 'overall_10' : 'All';
       sortAsc = false;
       updateBoard();
     });
     STRATUM_SELECT.addEventListener('change', () => {
-      sortKey = 'overall_9';
+      sortKey = 'overall_10';
       sortAsc = false;
       updateBoard();
     });
@@ -79,6 +81,7 @@ async function initMarkdown() {
   const targets = [
     ['intro-markdown', 'blobs/intro.md'],
     ['metrics-details', 'blobs/metrics.md'],
+    ['column-guide', 'blobs/columns.md'],
     ['submit-here', 'blobs/submitting.md'],
   ];
   await Promise.all(targets.map(async ([id, path]) => {
@@ -126,21 +129,23 @@ function buildBreakdownRows(groups) {
     .map((displayName) => strataData.All.find((row) => row.display_name === displayName))
     .filter(Boolean)
     .map((base) => {
-      const row = { ...base, All: base.overall_9, groupCoverage: {} };
+      const row = { ...base, All: base.overall_10, groupCoverage: {} };
       Object.entries(groups).forEach(([tag, scores]) => {
         const match = modelMap(scores)[base.model_id];
-        row[tag] = match?.overall_9 ?? null;
+        row[tag] = match?.overall_10 ?? null;
         row.groupCoverage[tag] = match ? `${match.n_scored}/${match.n_total}` : '0/0';
       });
-      row.All = overall[base.model_id]?.overall_9 ?? null;
+      row.All = overall[base.model_id]?.overall_10 ?? null;
       return row;
     });
 }
 
 function currentRows() {
-  if (BOARD_SELECT.value === 'domains') return buildBreakdownRows(domainData);
-  if (BOARD_SELECT.value === 'failure_modes') return buildBreakdownRows(failureModeData);
-  return [...(strataData[STRATUM_SELECT.value] || [])];
+  let rows;
+  if (BOARD_SELECT.value === 'domains') rows = buildBreakdownRows(domainData);
+  else if (BOARD_SELECT.value === 'failure_modes') rows = buildBreakdownRows(failureModeData);
+  else rows = [...(strataData[STRATUM_SELECT.value] || [])];
+  return rows.filter((row) => !EXCLUDED_MODELS.has(row.model_id));
 }
 
 function numericValue(row, key) {
@@ -173,17 +178,17 @@ function arrowFor(key) {
   return sortKey === key ? (sortAsc ? ' ↑' : ' ↓') : '';
 }
 
-function sortableHeader(key, label, className = '') {
-  return `<th class="${className}" data-sort="${escapeHtml(key)}">${escapeHtml(label)}${arrowFor(key)}</th>`;
+function sortableHeader(key, label, className = '', description = '') {
+  const title = description ? ` title="${escapeHtml(description)}"` : '';
+  return `<th class="${className}" data-sort="${escapeHtml(key)}"${title}>${escapeHtml(label)}${arrowFor(key)}</th>`;
 }
 
 function renderHeaders() {
-  let html = '<th class="rank-column">#</th>' + sortableHeader('display_name', 'Model', 'model-column');
+  let html = '<th class="rank-column">#</th>' + sortableHeader('display_name', 'Model', 'model-column', 'Evaluated image-generation model.');
   if (BOARD_SELECT.value === 'components') {
-    html += sortableHeader('overall_9', 'Overall-9', 'primary-metric');
-    html += sortableHeader('overall_10', 'Overall-10 (Paper)');
-    COMPONENTS.forEach(([key, label]) => { html += sortableHeader(`component:${key}`, label); });
-    html += sortableHeader('coverage', 'Coverage');
+    html += sortableHeader('overall_10', 'Overall-10', 'primary-metric', 'Prompt-macro average across the ten applicable components, scaled to 0–100.');
+    COMPONENTS.forEach(([key, label, description]) => { html += sortableHeader(`component:${key}`, label, '', description); });
+    html += sortableHeader('coverage', 'Coverage', '', 'Share and count of prompts with valid scored results.');
   } else {
     html += sortableHeader('All', 'All 751', 'primary-metric');
     const groups = BOARD_SELECT.value === 'domains' ? domainData : failureModeData;
@@ -219,8 +224,7 @@ function renderComponentRow(row, index) {
   return `<tr>
     <td class="rank-column">${index + 1}</td>
     ${modelCell(row)}
-    <td class="metric-cell">${formatScore(row.overall_9)}</td>
-    <td>${formatScore(row.overall_10)}</td>
+    <td class="metric-cell">${formatScore(row.overall_10)}</td>
     ${components}
     <td class="${coverageClass}" title="${row.n_scored} scored of ${row.n_total}; missing policy: ${escapeHtml(row.missing_policy)}">
       ${coveragePercent}% <span class="coverage-count">${row.n_scored}/${row.n_total}</span>

public/blobs/columns.md

@@ -0,0 +1,16 @@
+## Column guide
+
+- **Overall-10** — Prompt-macro average across the ten applicable components, scaled from 0–3 to 0–100.
+- **Checklist** — Satisfaction of prompt-specific verification checklist items.
+- **Rubric Adaptive** — Satisfaction of prompt-specific weighted evaluation-rubric criteria.
+- **Prompt Faithfulness** — How completely the image follows the user prompt.
+- **Image Quality** — Visual fidelity, clarity, detail, and absence of rendering defects.
+- **Text Rendering** — Correctness and legibility of text shown in the image.
+- **AI Naturalness** — How natural and non-synthetic the image appears.
+- **Composition & Aesthetics** — Layout, balance, coherence, and aesthetic quality.
+- **Physical Plausibility** — Consistency with real-world geometry, anatomy, lighting, and physics.
+- **Visual Reference** — Consistency with required visual-reference entities or attributes.
+- **Text Reference** — Factual consistency with required text-derived knowledge.
+- **Coverage** — Percentage and count of prompts with valid scored results. Missing-result handling follows the model-specific policy described in Metric Details.
+
+All score columns use the 0–100 public scale. **N/A** means a component is not applicable, not a score of zero.

public/blobs/intro.md

@@ -1,5 +1,7 @@
-**SearchGen-Bench** evaluates image generators on 751 prompts spanning 22 domains and 12 failure modes. It separates prompts that generators can answer without retrieval from visually and textually search-intensive prompts.
+## Where visual generators know—and where they need search
 
-The primary leaderboard metric, **Overall-9**, is the prompt-macro average of nine physical-plausibility judge components. The paper-compatible **Overall-10** additionally includes Text Reference. Use the scoreboard selector to inspect component, domain, and failure-mode rankings.
+**SearchGen-Bench** compares image generators across 751 evaluation prompts, knowledge-boundary strata, 22 domains, and 12 recurring failure modes. The benchmark separates 100 **NoSearch** prompts that strong generators can answer from parametric knowledge from 651 **SearchIntensive** prompts whose visual or textual requirements expose gaps that retrieval can address.
+
+The primary metric is **Overall-10**: a prompt-macro average over the canonical ten applicable FF-judge+PP components, reported on a 0–100 scale. Use the scoreboard selector to inspect results by component, domain, or failure mode.
 
 All scores are generated from versioned prompt-level records. Counts and coverage are shown because domains and failure modes are multi-label and some commercial generators have incomplete evaluations.

public/blobs/metrics.md

@@ -1,8 +1,6 @@
 ## Metric details
 
-**Overall-9** is the mean of all applicable public components for each prompt, followed by a macro average over prompts and conversion from the raw 0–3 scale to 0–100. Its components are Checklist, Rubric Adaptive, Prompt Faithfulness, Image Quality, Text Rendering, AI Naturalness, Composition and Aesthetics, Physical Plausibility, and Visual Reference.
-
-**Overall-10 (Paper)** uses the same procedure but additionally includes Text Reference. It is retained so results can be reconciled with the paper's canonical tables.
+**Overall-10** is the primary benchmark metric. For each prompt, it averages all applicable values across Checklist, Rubric Adaptive, Prompt Faithfulness, Image Quality, Text Rendering, AI Naturalness, Composition and Aesthetics, Physical Plausibility, Visual Reference, and Text Reference. Prompt-level means are then macro-averaged and converted from the raw 0–3 scale to 0–100.
 
 An inapplicable component is excluded from its prompt-level mean. Missing model results are zero-filled by default, matching the canonical paper convention. Missing Grok-Imagine-Image and Qwen-Image-2-Pro results are excluded from their denominators. Coverage always reports valid scored prompts over prompts in the selected group.
 

public/data/leaderboard_by_failure_mode.json

@@ -9,6 +9,7 @@
         "physical_plausibility": 415,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 336,
         "text_rendering": 376,
         "visual_reference_evaluation": 439
       },
@@ -20,6 +21,7 @@
         "physical_plausibility": 73.8,
         "prompt_faithfulness": 68.5,
         "rubric_adaptive": 69.7,
+        "text_reference_evaluation": 55.3,
         "text_rendering": 73.2,
         "visual_reference_evaluation": 66.6
       },
@@ -43,6 +45,7 @@
         "physical_plausibility": 455,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 327,
         "text_rendering": 344,
         "visual_reference_evaluation": 437
       },
@@ -54,6 +57,7 @@
         "physical_plausibility": 76.2,
         "prompt_faithfulness": 62.2,
         "rubric_adaptive": 65.8,
+        "text_reference_evaluation": 49.5,
         "text_rendering": 66.4,
         "visual_reference_evaluation": 61.6
       },
@@ -77,6 +81,7 @@
         "physical_plausibility": 389,
         "prompt_faithfulness": 504,
         "rubric_adaptive": 504,
+        "text_reference_evaluation": 331,
         "text_rendering": 355,
         "visual_reference_evaluation": 417
       },
@@ -88,6 +93,7 @@
         "physical_plausibility": 69.9,
         "prompt_faithfulness": 61.3,
         "rubric_adaptive": 63.8,
+        "text_reference_evaluation": 46.6,
         "text_rendering": 61.7,
         "visual_reference_evaluation": 60.7
       },
@@ -111,6 +117,7 @@
         "physical_plausibility": 410,
         "prompt_faithfulness": 526,
         "rubric_adaptive": 526,
+        "text_reference_evaluation": 320,
         "text_rendering": 321,
         "visual_reference_evaluation": 439
       },
@@ -122,6 +129,7 @@
         "physical_plausibility": 70.2,
         "prompt_faithfulness": 50.8,
         "rubric_adaptive": 54.7,
+        "text_reference_evaluation": 37.6,
         "text_rendering": 56.9,
         "visual_reference_evaluation": 47.0
       },
@@ -145,6 +153,7 @@
         "physical_plausibility": 422,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 335,
         "text_rendering": 319,
         "visual_reference_evaluation": 448
       },
@@ -156,6 +165,7 @@
         "physical_plausibility": 65.3,
         "prompt_faithfulness": 47.5,
         "rubric_adaptive": 51.6,
+        "text_reference_evaluation": 33.8,
         "text_rendering": 52.0,
         "visual_reference_evaluation": 44.0
       },
@@ -179,6 +189,7 @@
         "physical_plausibility": 441,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 336,
         "text_rendering": 353,
         "visual_reference_evaluation": 446
       },
@@ -190,6 +201,7 @@
         "physical_plausibility": 62.1,
         "prompt_faithfulness": 46.1,
         "rubric_adaptive": 50.8,
+        "text_reference_evaluation": 29.1,
         "text_rendering": 48.6,
         "visual_reference_evaluation": 41.3
       },
@@ -213,6 +225,7 @@
         "physical_plausibility": 445,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 343,
         "text_rendering": 333,
         "visual_reference_evaluation": 436
       },
@@ -224,6 +237,7 @@
         "physical_plausibility": 64.5,
         "prompt_faithfulness": 41.4,
         "rubric_adaptive": 47.1,
+        "text_reference_evaluation": 23.7,
         "text_rendering": 37.8,
         "visual_reference_evaluation": 39.6
       },
@@ -247,6 +261,7 @@
         "physical_plausibility": 427,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 358,
         "text_rendering": 346,
         "visual_reference_evaluation": 437
       },
@@ -258,6 +273,7 @@
         "physical_plausibility": 63.3,
         "prompt_faithfulness": 39.6,
         "rubric_adaptive": 44.3,
+        "text_reference_evaluation": 18.3,
         "text_rendering": 29.3,
         "visual_reference_evaluation": 38.4
       },
@@ -281,6 +297,7 @@
         "physical_plausibility": 486,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 355,
         "text_rendering": 328,
         "visual_reference_evaluation": 435
       },
@@ -292,6 +309,7 @@
         "physical_plausibility": 48.5,
         "prompt_faithfulness": 25.9,
         "rubric_adaptive": 32.0,
+        "text_reference_evaluation": 7.9,
         "text_rendering": 11.4,
         "visual_reference_evaluation": 25.4
       },
@@ -315,6 +333,7 @@
         "physical_plausibility": 440,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 365,
         "text_rendering": 345,
         "visual_reference_evaluation": 436
       },
@@ -326,6 +345,7 @@
         "physical_plausibility": 51.2,
         "prompt_faithfulness": 23.0,
         "rubric_adaptive": 29.1,
+        "text_reference_evaluation": 6.6,
         "text_rendering": 8.7,
         "visual_reference_evaluation": 23.0
       },
@@ -349,6 +369,7 @@
         "physical_plausibility": 442,
         "prompt_faithfulness": 533,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 366,
         "text_rendering": 327,
         "visual_reference_evaluation": 434
       },
@@ -360,6 +381,7 @@
         "physical_plausibility": 48.1,
         "prompt_faithfulness": 17.0,
         "rubric_adaptive": 23.4,
+        "text_reference_evaluation": 3.4,
         "text_rendering": 4.5,
         "visual_reference_evaluation": 16.3
       },
@@ -383,6 +405,7 @@
         "physical_plausibility": 460,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 353,
         "text_rendering": 313,
         "visual_reference_evaluation": 435
       },
@@ -394,6 +417,7 @@
         "physical_plausibility": 41.4,
         "prompt_faithfulness": 18.4,
         "rubric_adaptive": 23.2,
+        "text_reference_evaluation": 3.4,
         "text_rendering": 4.1,
         "visual_reference_evaluation": 19.0
       },
@@ -417,6 +441,7 @@
         "physical_plausibility": 473,
         "prompt_faithfulness": 534,
         "rubric_adaptive": 534,
+        "text_reference_evaluation": 449,
         "text_rendering": 430,
         "visual_reference_evaluation": 506
       },
@@ -428,6 +453,7 @@
         "physical_plausibility": 17.3,
         "prompt_faithfulness": 6.0,
         "rubric_adaptive": 8.1,
+        "text_reference_evaluation": 0.9,
         "text_rendering": 0.9,
         "visual_reference_evaluation": 5.9
       },
@@ -453,6 +479,7 @@
         "physical_plausibility": 144,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 91,
         "text_rendering": 95,
         "visual_reference_evaluation": 121
       },
@@ -464,6 +491,7 @@
         "physical_plausibility": 75.3,
         "prompt_faithfulness": 68.3,
         "rubric_adaptive": 71.3,
+        "text_reference_evaluation": 50.4,
         "text_rendering": 70.9,
         "visual_reference_evaluation": 62.4
       },
@@ -487,6 +515,7 @@
         "physical_plausibility": 149,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 86,
         "text_rendering": 78,
         "visual_reference_evaluation": 121
       },
@@ -498,6 +527,7 @@
         "physical_plausibility": 77.9,
         "prompt_faithfulness": 63.1,
         "rubric_adaptive": 68.7,
+        "text_reference_evaluation": 47.1,
         "text_rendering": 61.3,
         "visual_reference_evaluation": 59.5
       },
@@ -521,6 +551,7 @@
         "physical_plausibility": 136,
         "prompt_faithfulness": 153,
         "rubric_adaptive": 153,
+        "text_reference_evaluation": 90,
         "text_rendering": 92,
         "visual_reference_evaluation": 121
       },
@@ -532,6 +563,7 @@
         "physical_plausibility": 71.3,
         "prompt_faithfulness": 63.8,
         "rubric_adaptive": 68.1,
+        "text_reference_evaluation": 48.0,
         "text_rendering": 64.7,
         "visual_reference_evaluation": 61.0
       },
@@ -555,6 +587,7 @@
         "physical_plausibility": 139,
         "prompt_faithfulness": 158,
         "rubric_adaptive": 158,
+        "text_reference_evaluation": 85,
         "text_rendering": 70,
         "visual_reference_evaluation": 124
       },
@@ -566,6 +599,7 @@
         "physical_plausibility": 71.0,
         "prompt_faithfulness": 54.7,
         "rubric_adaptive": 62.6,
+        "text_reference_evaluation": 45.7,
         "text_rendering": 65.5,
         "visual_reference_evaluation": 53.2
       },
@@ -589,6 +623,7 @@
         "physical_plausibility": 139,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 86,
         "text_rendering": 73,
         "visual_reference_evaluation": 126
       },
@@ -600,6 +635,7 @@
         "physical_plausibility": 69.3,
         "prompt_faithfulness": 54.8,
         "rubric_adaptive": 61.9,
+        "text_reference_evaluation": 41.3,
         "text_rendering": 60.7,
         "visual_reference_evaluation": 53.8
       },
@@ -623,6 +659,7 @@
         "physical_plausibility": 141,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 88,
         "text_rendering": 75,
         "visual_reference_evaluation": 121
       },
@@ -634,6 +671,7 @@
         "physical_plausibility": 70.7,
         "prompt_faithfulness": 51.2,
         "rubric_adaptive": 57.5,
+        "text_reference_evaluation": 32.0,
         "text_rendering": 49.6,
         "visual_reference_evaluation": 50.0
       },
@@ -657,6 +695,7 @@
         "physical_plausibility": 139,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 90,
         "text_rendering": 86,
         "visual_reference_evaluation": 126
       },
@@ -668,6 +707,7 @@
         "physical_plausibility": 70.0,
         "prompt_faithfulness": 53.6,
         "rubric_adaptive": 58.6,
+        "text_reference_evaluation": 35.4,
         "text_rendering": 54.5,
         "visual_reference_evaluation": 48.3
       },
@@ -691,6 +731,7 @@
         "physical_plausibility": 143,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 97,
         "text_rendering": 79,
         "visual_reference_evaluation": 121
       },
@@ -702,6 +743,7 @@
         "physical_plausibility": 68.1,
         "prompt_faithfulness": 44.5,
         "rubric_adaptive": 52.5,
+        "text_reference_evaluation": 16.2,
         "text_rendering": 20.8,
         "visual_reference_evaluation": 42.8
       },
@@ -725,6 +767,7 @@
         "physical_plausibility": 153,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 92,
         "text_rendering": 74,
         "visual_reference_evaluation": 121
       },
@@ -736,6 +779,7 @@
         "physical_plausibility": 60.1,
         "prompt_faithfulness": 38.4,
         "rubric_adaptive": 44.8,
+        "text_reference_evaluation": 16.1,
         "text_rendering": 21.2,
         "visual_reference_evaluation": 39.9
       },
@@ -759,6 +803,7 @@
         "physical_plausibility": 143,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 98,
         "text_rendering": 81,
         "visual_reference_evaluation": 121
       },
@@ -770,6 +815,7 @@
         "physical_plausibility": 60.5,
         "prompt_faithfulness": 32.0,
         "rubric_adaptive": 39.4,
+        "text_reference_evaluation": 9.2,
         "text_rendering": 6.8,
         "visual_reference_evaluation": 33.3
       },
@@ -793,6 +839,7 @@
         "physical_plausibility": 140,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 101,
         "text_rendering": 79,
         "visual_reference_evaluation": 121
       },
@@ -804,6 +851,7 @@
         "physical_plausibility": 58.2,
         "prompt_faithfulness": 23.3,
         "rubric_adaptive": 31.3,
+        "text_reference_evaluation": 6.8,
         "text_rendering": 4.2,
         "visual_reference_evaluation": 22.6
       },
@@ -827,6 +875,7 @@
         "physical_plausibility": 142,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 98,
         "text_rendering": 70,
         "visual_reference_evaluation": 121
       },
@@ -838,6 +887,7 @@
         "physical_plausibility": 49.4,
         "prompt_faithfulness": 24.3,
         "rubric_adaptive": 30.4,
+        "text_reference_evaluation": 7.3,
         "text_rendering": 2.6,
         "visual_reference_evaluation": 24.8
       },
@@ -861,6 +911,7 @@
         "physical_plausibility": 151,
         "prompt_faithfulness": 159,
         "rubric_adaptive": 159,
+        "text_reference_evaluation": 136,
         "text_rendering": 124,
         "visual_reference_evaluation": 147
       },
@@ -872,6 +923,7 @@
         "physical_plausibility": 19.6,
         "prompt_faithfulness": 6.1,
         "rubric_adaptive": 8.3,
+        "text_reference_evaluation": 0.7,
         "text_rendering": 0.7,
         "visual_reference_evaluation": 6.3
       },
@@ -897,6 +949,7 @@
         "physical_plausibility": 193,
         "prompt_faithfulness": 281,
         "rubric_adaptive": 281,
+        "text_reference_evaluation": 197,
         "text_rendering": 226,
         "visual_reference_evaluation": 224
       },
@@ -908,6 +961,7 @@
         "physical_plausibility": 81.0,
         "prompt_faithfulness": 71.9,
         "rubric_adaptive": 72.6,
+        "text_reference_evaluation": 62.1,
         "text_rendering": 78.8,
         "visual_reference_evaluation": 67.3
       },
@@ -931,6 +985,7 @@
         "physical_plausibility": 221,
         "prompt_faithfulness": 281,
         "rubric_adaptive": 281,
+        "text_reference_evaluation": 202,
         "text_rendering": 210,
         "visual_reference_evaluation": 223
       },
@@ -942,6 +997,7 @@
         "physical_plausibility": 80.9,
         "prompt_faithfulness": 62.9,
         "rubric_adaptive": 64.5,
+        "text_reference_evaluation": 51.7,
         "text_rendering": 67.1,
         "visual_reference_evaluation": 59.2
       },
@@ -965,6 +1021,7 @@
         "physical_plausibility": 181,
         "prompt_faithfulness": 269,
         "rubric_adaptive": 269,
+        "text_reference_evaluation": 202,
         "text_rendering": 218,
         "visual_reference_evaluation": 221
       },
@@ -976,6 +1033,7 @@
         "physical_plausibility": 76.4,
         "prompt_faithfulness": 63.5,
         "rubric_adaptive": 63.6,
+        "text_reference_evaluation": 47.4,
         "text_rendering": 62.9,
         "visual_reference_evaluation": 57.5
       },
@@ -999,6 +1057,7 @@
         "physical_plausibility": 190,
         "prompt_faithfulness": 277,
         "rubric_adaptive": 277,
+        "text_reference_evaluation": 196,
         "text_rendering": 208,
         "visual_reference_evaluation": 229
       },
@@ -1010,6 +1069,7 @@
         "physical_plausibility": 72.5,
         "prompt_faithfulness": 52.2,
         "rubric_adaptive": 53.8,
+        "text_reference_evaluation": 38.4,
         "text_rendering": 58.7,
         "visual_reference_evaluation": 44.8
       },
@@ -1033,6 +1093,7 @@
         "physical_plausibility": 199,
         "prompt_faithfulness": 281,
         "rubric_adaptive": 281,
+        "text_reference_evaluation": 203,
         "text_rendering": 203,
         "visual_reference_evaluation": 234
       },
@@ -1044,6 +1105,7 @@
         "physical_plausibility": 66.3,
         "prompt_faithfulness": 49.7,
         "rubric_adaptive": 51.8,
+        "text_reference_evaluation": 35.5,
         "text_rendering": 56.2,
         "visual_reference_evaluation": 41.3
       },
@@ -1067,6 +1129,7 @@
         "physical_plausibility": 212,
         "prompt_faithfulness": 281,
         "rubric_adaptive": 281,
+        "text_reference_evaluation": 204,
         "text_rendering": 220,
         "visual_reference_evaluation": 233
       },
@@ -1078,6 +1141,7 @@
         "physical_plausibility": 62.6,
         "prompt_faithfulness": 42.3,
         "rubric_adaptive": 47.0,
+        "text_reference_evaluation": 27.7,
         "text_rendering": 47.3,
         "visual_reference_evaluation": 35.6
       },
@@ -1101,6 +1165,7 @@
         "physical_plausibility": 217,
         "prompt_faithfulness": 280,
         "rubric_adaptive": 281,
+        "text_reference_evaluation": 215,
         "text_rendering": 208,
         "visual_reference_evaluation": 223
       },
@@ -1112,6 +1177,7 @@
         "physical_plausibility": 61.5,
         "prompt_faithfulness": 37.7,
         "rubric_adaptive": 42.8,
+        "text_reference_evaluation": 24.1,
         "text_rendering": 35.8,
         "visual_reference_evaluation": 33.5
       },
@@ -1135,6 +1201,7 @@
         "physical_plausibility": 205,
         "prompt_faithfulness": 281,
         "rubric_adaptive": 281,
+        "text_reference_evaluation": 220,
         "text_rendering": 216,
         "visual_reference_evaluation": 223
       },
@@ -1146,6 +1213,7 @@
         "physical_plausibility": 66.7,
         "prompt_faithfulness": 36.6,
         "rubric_adaptive": 40.3,
+        "text_reference_evaluation": 17.6,
         "text_rendering": 26.9,
         "visual_reference_evaluation": 32.2
       },
@@ -1169,6 +1237,7 @@
         "physical_plausibility": 250,
         "prompt_faithfulness": 281,
         "rubric_adaptive": 281,
+        "text_reference_evaluation": 217,
         "text_rendering": 206,
         "visual_reference_evaluation": 223
       },
@@ -1180,6 +1249,7 @@
         "physical_plausibility": 44.9,
         "prompt_faithfulness": 20.8,
         "rubric_adaptive": 25.9,
+        "text_reference_evaluation": 8.0,
         "text_rendering": 11.2,
         "visual_reference_evaluation": 18.4
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@@ -1203,6 +1273,7 @@
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public/data/leaderboard_by_stratum.json

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         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 260,
         "text_rendering": 250,
         "visual_reference_evaluation": 172
       },
@@ -1556,6 +1647,7 @@
         "physical_plausibility": 72.3,
         "prompt_faithfulness": 33.6,
         "rubric_adaptive": 36.7,
+        "text_reference_evaluation": 16.3,
         "text_rendering": 30.1,
         "visual_reference_evaluation": 24.0
       },
@@ -1579,6 +1671,7 @@
         "physical_plausibility": 188,
         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 261,
         "text_rendering": 254,
         "visual_reference_evaluation": 172
       },
@@ -1590,6 +1683,7 @@
         "physical_plausibility": 75.5,
         "prompt_faithfulness": 32.5,
         "rubric_adaptive": 33.7,
+        "text_reference_evaluation": 12.1,
         "text_rendering": 22.1,
         "visual_reference_evaluation": 25.0
       },
@@ -1613,6 +1707,7 @@
         "physical_plausibility": 233,
         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 264,
         "text_rendering": 253,
         "visual_reference_evaluation": 172
       },
@@ -1624,6 +1719,7 @@
         "physical_plausibility": 44.3,
         "prompt_faithfulness": 13.8,
         "rubric_adaptive": 17.5,
+        "text_reference_evaluation": 3.5,
         "text_rendering": 5.4,
         "visual_reference_evaluation": 10.4
       },
@@ -1647,6 +1743,7 @@
         "physical_plausibility": 198,
         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 263,
         "text_rendering": 254,
         "visual_reference_evaluation": 172
       },
@@ -1658,6 +1755,7 @@
         "physical_plausibility": 48.7,
         "prompt_faithfulness": 12.4,
         "rubric_adaptive": 16.2,
+        "text_reference_evaluation": 3.6,
         "text_rendering": 3.9,
         "visual_reference_evaluation": 9.9
       },
@@ -1681,6 +1779,7 @@
         "physical_plausibility": 201,
         "prompt_faithfulness": 263,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 262,
         "text_rendering": 249,
         "visual_reference_evaluation": 171
       },
@@ -1692,6 +1791,7 @@
         "physical_plausibility": 44.6,
         "prompt_faithfulness": 9.1,
         "rubric_adaptive": 13.6,
+        "text_reference_evaluation": 1.7,
         "text_rendering": 2.8,
         "visual_reference_evaluation": 7.2
       },
@@ -1715,6 +1815,7 @@
         "physical_plausibility": 203,
         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 264,
         "text_rendering": 244,
         "visual_reference_evaluation": 172
       },
@@ -1726,6 +1827,7 @@
         "physical_plausibility": 37.8,
         "prompt_faithfulness": 9.9,
         "rubric_adaptive": 12.4,
+        "text_reference_evaluation": 1.1,
         "text_rendering": 1.6,
         "visual_reference_evaluation": 9.3
       },
@@ -1749,6 +1851,7 @@
         "physical_plausibility": 216,
         "prompt_faithfulness": 264,
         "rubric_adaptive": 264,
+        "text_reference_evaluation": 264,
         "text_rendering": 249,
         "visual_reference_evaluation": 239
       },
@@ -1760,6 +1863,7 @@
         "physical_plausibility": 8.1,
         "prompt_faithfulness": 0.6,
         "rubric_adaptive": 1.7,
+        "text_reference_evaluation": 0.2,
         "text_rendering": 0.0,
         "visual_reference_evaluation": 0.1
       },
@@ -1785,6 +1889,7 @@
         "physical_plausibility": 305,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 194,
         "text_rendering": 260,
         "visual_reference_evaluation": 333
       },
@@ -1796,6 +1901,7 @@
         "physical_plausibility": 71.2,
         "prompt_faithfulness": 69.2,
         "rubric_adaptive": 71.7,
+        "text_reference_evaluation": 63.7,
         "text_rendering": 81.5,
         "visual_reference_evaluation": 65.7
       },
@@ -1819,6 +1925,7 @@
         "physical_plausibility": 319,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 190,
         "text_rendering": 223,
         "visual_reference_evaluation": 333
       },
@@ -1830,6 +1937,7 @@
         "physical_plausibility": 73.3,
         "prompt_faithfulness": 61.1,
         "rubric_adaptive": 65.4,
+        "text_reference_evaluation": 55.6,
         "text_rendering": 70.8,
         "visual_reference_evaluation": 60.4
       },
@@ -1853,6 +1961,7 @@
         "physical_plausibility": 278,
         "prompt_faithfulness": 356,
         "rubric_adaptive": 356,
+        "text_reference_evaluation": 194,
         "text_rendering": 236,
         "visual_reference_evaluation": 321
       },
@@ -1864,6 +1973,7 @@
         "physical_plausibility": 66.5,
         "prompt_faithfulness": 60.8,
         "rubric_adaptive": 64.9,
+        "text_reference_evaluation": 54.6,
         "text_rendering": 69.0,
         "visual_reference_evaluation": 60.2
       },
@@ -1887,6 +1997,7 @@
         "physical_plausibility": 293,
         "prompt_faithfulness": 378,
         "rubric_adaptive": 378,
+        "text_reference_evaluation": 178,
         "text_rendering": 196,
         "visual_reference_evaluation": 343
       },
@@ -1898,6 +2009,7 @@
         "physical_plausibility": 65.8,
         "prompt_faithfulness": 47.9,
         "rubric_adaptive": 54.1,
+        "text_reference_evaluation": 41.9,
         "text_rendering": 66.0,
         "visual_reference_evaluation": 47.2
       },
@@ -1921,6 +2033,7 @@
         "physical_plausibility": 308,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 200,
         "text_rendering": 200,
         "visual_reference_evaluation": 353
       },
@@ -1932,6 +2045,7 @@
         "physical_plausibility": 60.3,
         "prompt_faithfulness": 44.0,
         "rubric_adaptive": 50.2,
+        "text_reference_evaluation": 39.9,
         "text_rendering": 62.0,
         "visual_reference_evaluation": 43.2
       },
@@ -1955,6 +2069,7 @@
         "physical_plausibility": 308,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 194,
         "text_rendering": 225,
         "visual_reference_evaluation": 351
       },
@@ -1966,6 +2081,7 @@
         "physical_plausibility": 58.3,
         "prompt_faithfulness": 44.8,
         "rubric_adaptive": 50.3,
+        "text_reference_evaluation": 33.2,
         "text_rendering": 54.4,
         "visual_reference_evaluation": 41.9
       },
@@ -1989,6 +2105,7 @@
         "physical_plausibility": 312,
         "prompt_faithfulness": 386,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 203,
         "text_rendering": 203,
         "visual_reference_evaluation": 332
       },
@@ -2000,6 +2117,7 @@
         "physical_plausibility": 58.8,
         "prompt_faithfulness": 41.9,
         "rubric_adaptive": 48.3,
+        "text_reference_evaluation": 28.5,
         "text_rendering": 43.2,
         "visual_reference_evaluation": 40.8
       },
@@ -2023,6 +2141,7 @@
         "physical_plausibility": 314,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 221,
         "text_rendering": 214,
         "visual_reference_evaluation": 333
       },
@@ -2034,6 +2153,7 @@
         "physical_plausibility": 59.5,
         "prompt_faithfulness": 38.4,
         "rubric_adaptive": 45.0,
+        "text_reference_evaluation": 23.0,
         "text_rendering": 35.0,
         "visual_reference_evaluation": 37.4
       },
@@ -2057,6 +2177,7 @@
         "physical_plausibility": 350,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 214,
         "text_rendering": 199,
         "visual_reference_evaluation": 331
       },
@@ -2068,6 +2189,7 @@
         "physical_plausibility": 44.8,
         "prompt_faithfulness": 21.9,
         "rubric_adaptive": 29.0,
+        "text_reference_evaluation": 6.9,
         "text_rendering": 12.8,
         "visual_reference_evaluation": 21.6
       },
@@ -2091,6 +2213,7 @@
         "physical_plausibility": 305,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 231,
         "text_rendering": 222,
         "visual_reference_evaluation": 332
       },
@@ -2102,6 +2225,7 @@
         "physical_plausibility": 48.5,
         "prompt_faithfulness": 20.4,
         "rubric_adaptive": 27.7,
+        "text_reference_evaluation": 7.2,
         "text_rendering": 11.0,
         "visual_reference_evaluation": 20.6
       },
@@ -2125,6 +2249,7 @@
         "physical_plausibility": 301,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 235,
         "text_rendering": 210,
         "visual_reference_evaluation": 331
       },
@@ -2136,6 +2261,7 @@
         "physical_plausibility": 47.3,
         "prompt_faithfulness": 14.7,
         "rubric_adaptive": 21.7,
+        "text_reference_evaluation": 3.0,
         "text_rendering": 6.0,
         "visual_reference_evaluation": 14.3
       },
@@ -2159,6 +2285,7 @@
         "physical_plausibility": 333,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 215,
         "text_rendering": 192,
         "visual_reference_evaluation": 331
       },
@@ -2170,6 +2297,7 @@
         "physical_plausibility": 36.2,
         "prompt_faithfulness": 15.5,
         "rubric_adaptive": 21.2,
+        "text_reference_evaluation": 2.9,
         "text_rendering": 3.6,
         "visual_reference_evaluation": 15.7
       },
@@ -2193,6 +2321,7 @@
         "physical_plausibility": 340,
         "prompt_faithfulness": 387,
         "rubric_adaptive": 387,
+        "text_reference_evaluation": 266,
         "text_rendering": 247,
         "visual_reference_evaluation": 349
       },
@@ -2204,6 +2333,7 @@
         "physical_plausibility": 33.5,
         "prompt_faithfulness": 11.2,
         "rubric_adaptive": 15.7,
+        "text_reference_evaluation": 2.6,
         "text_rendering": 2.8,
         "visual_reference_evaluation": 11.7
       },

public/data/leaderboard_overall.json

@@ -8,6 +8,7 @@
       "physical_plausibility": 558,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 486,
       "text_rendering": 544,
       "visual_reference_evaluation": 599
     },
@@ -19,6 +20,7 @@
       "physical_plausibility": 76.7,
       "prompt_faithfulness": 69.4,
       "rubric_adaptive": 70.8,
+      "text_reference_evaluation": 54.6,
       "text_rendering": 75.4,
       "visual_reference_evaluation": 65.7
     },
@@ -42,6 +44,7 @@
       "physical_plausibility": 627,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 480,
       "text_rendering": 500,
       "visual_reference_evaluation": 598
     },
@@ -53,6 +56,7 @@
       "physical_plausibility": 78.4,
       "prompt_faithfulness": 62.3,
       "rubric_adaptive": 65.1,
+      "text_reference_evaluation": 47.4,
       "text_rendering": 66.3,
       "visual_reference_evaluation": 59.8
     },
@@ -76,6 +80,7 @@
       "physical_plausibility": 539,
       "prompt_faithfulness": 717,
       "rubric_adaptive": 717,
+      "text_reference_evaluation": 487,
       "text_rendering": 517,
       "visual_reference_evaluation": 582
     },
@@ -87,6 +92,7 @@
       "physical_plausibility": 73.1,
       "prompt_faithfulness": 62.0,
       "rubric_adaptive": 64.1,
+      "text_reference_evaluation": 46.0,
       "text_rendering": 63.4,
       "visual_reference_evaluation": 58.9
     },
@@ -110,6 +116,7 @@
       "physical_plausibility": 544,
       "prompt_faithfulness": 742,
       "rubric_adaptive": 742,
+      "text_reference_evaluation": 473,
       "text_rendering": 471,
       "visual_reference_evaluation": 606
     },
@@ -121,6 +128,7 @@
       "physical_plausibility": 71.7,
       "prompt_faithfulness": 50.0,
       "rubric_adaptive": 54.2,
+      "text_reference_evaluation": 35.7,
       "text_rendering": 56.7,
       "visual_reference_evaluation": 46.2
     },
@@ -144,6 +152,7 @@
       "physical_plausibility": 561,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 492,
       "text_rendering": 467,
       "visual_reference_evaluation": 617
     },
@@ -155,6 +164,7 @@
       "physical_plausibility": 67.9,
       "prompt_faithfulness": 47.3,
       "rubric_adaptive": 51.9,
+      "text_reference_evaluation": 33.1,
       "text_rendering": 54.0,
       "visual_reference_evaluation": 43.2
     },
@@ -178,6 +188,7 @@
       "physical_plausibility": 593,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 486,
       "text_rendering": 518,
       "visual_reference_evaluation": 615
     },
@@ -189,6 +200,7 @@
       "physical_plausibility": 64.0,
       "prompt_faithfulness": 45.9,
       "rubric_adaptive": 50.2,
+      "text_reference_evaluation": 28.2,
       "text_rendering": 48.9,
       "visual_reference_evaluation": 39.9
     },
@@ -212,6 +224,7 @@
       "physical_plausibility": 604,
       "prompt_faithfulness": 750,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 501,
       "text_rendering": 483,
       "visual_reference_evaluation": 596
     },
@@ -223,6 +236,7 @@
       "physical_plausibility": 65.6,
       "prompt_faithfulness": 41.6,
       "rubric_adaptive": 47.2,
+      "text_reference_evaluation": 23.4,
       "text_rendering": 38.1,
       "visual_reference_evaluation": 38.4
     },
@@ -246,6 +260,7 @@
       "physical_plausibility": 594,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 522,
       "text_rendering": 498,
       "visual_reference_evaluation": 597
     },
@@ -257,6 +272,7 @@
       "physical_plausibility": 66.0,
       "prompt_faithfulness": 39.1,
       "rubric_adaptive": 44.0,
+      "text_reference_evaluation": 17.8,
       "text_rendering": 28.9,
       "visual_reference_evaluation": 36.4
     },
@@ -280,6 +296,7 @@
       "physical_plausibility": 676,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 516,
       "text_rendering": 475,
       "visual_reference_evaluation": 595
     },
@@ -291,6 +308,7 @@
       "physical_plausibility": 48.6,
       "prompt_faithfulness": 24.5,
       "rubric_adaptive": 30.5,
+      "text_reference_evaluation": 7.7,
       "text_rendering": 11.3,
       "visual_reference_evaluation": 23.8
     },
@@ -314,6 +332,7 @@
       "physical_plausibility": 599,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 536,
       "text_rendering": 501,
       "visual_reference_evaluation": 596
     },
@@ -325,6 +344,7 @@
       "physical_plausibility": 51.5,
       "prompt_faithfulness": 21.7,
       "rubric_adaptive": 27.9,
+      "text_reference_evaluation": 6.6,
       "text_rendering": 8.4,
       "visual_reference_evaluation": 21.1
     },
@@ -348,6 +368,7 @@
       "physical_plausibility": 597,
       "prompt_faithfulness": 750,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 537,
       "text_rendering": 483,
       "visual_reference_evaluation": 594
     },
@@ -359,6 +380,7 @@
       "physical_plausibility": 49.0,
       "prompt_faithfulness": 16.0,
       "rubric_adaptive": 22.9,
+      "text_reference_evaluation": 3.6,
       "text_rendering": 4.7,
       "visual_reference_evaluation": 15.1
     },
@@ -382,6 +404,7 @@
       "physical_plausibility": 631,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 521,
       "text_rendering": 465,
       "visual_reference_evaluation": 595
     },
@@ -393,6 +416,7 @@
       "physical_plausibility": 40.4,
       "prompt_faithfulness": 16.7,
       "rubric_adaptive": 21.8,
+      "text_reference_evaluation": 3.5,
       "text_rendering": 3.5,
       "visual_reference_evaluation": 16.8
     },
@@ -416,6 +440,7 @@
       "physical_plausibility": 656,
       "prompt_faithfulness": 751,
       "rubric_adaptive": 751,
+      "text_reference_evaluation": 630,
       "text_rendering": 596,
       "visual_reference_evaluation": 688
     },
@@ -427,6 +452,7 @@
       "physical_plausibility": 20.0,
       "prompt_faithfulness": 6.0,
       "rubric_adaptive": 8.7,
+      "text_reference_evaluation": 1.2,
       "text_rendering": 1.2,
       "visual_reference_evaluation": 6.0
     },

public/data/manifest.json

@@ -88,7 +88,6 @@
   },
   "schema_version": "1.0.0",
   "scoring": {
-    "excluded_public_component": "text_reference_evaluation",
     "missing_policy_default": "zero_fill",
     "missing_policy_exceptions": [
       "qwen_image_2_pro",
@@ -117,6 +116,8 @@
       "physical_plausibility",
       "visual_reference_evaluation"
     ],
+    "overall_9_excluded_component": "text_reference_evaluation",
+    "primary_metric": "overall_10",
     "public_rounding_decimals": 1,
     "scale_public": [
       0,

scripts/build_leaderboard_data.py

@@ -14,7 +14,7 @@ from pathlib import Path
 from typing import Any, Callable
 
 
-PUBLIC_COMPONENTS = [
+OVERALL_9_COMPONENTS = [
     "checklist",
     "rubric_adaptive",
     "prompt_faithfulness",
@@ -25,7 +25,8 @@ PUBLIC_COMPONENTS = [
     "physical_plausibility",
     "visual_reference_evaluation",
 ]
-EXCLUDED_PUBLIC_COMPONENT = "text_reference_evaluation"
+OVERALL_9_EXCLUDED_COMPONENT = "text_reference_evaluation"
+DISPLAY_COMPONENTS = [*OVERALL_9_COMPONENTS, OVERALL_9_EXCLUDED_COMPONENT]
 
 MODEL_METADATA = {
     "bagel": ("Bagel", "Open"),
@@ -154,7 +155,7 @@ def load_score(row_dir: Path, model_id: str, canonical: Any) -> dict[str, Any]:
         "lane": "none",
         "components_raw_0to3": components,
         "overall_10_raw": mean_present(components, list(canonical.COMPONENT_KEYS)),
-        "overall_9_raw": mean_present(components, PUBLIC_COMPONENTS),
+        "overall_9_raw": mean_present(components, OVERALL_9_COMPONENTS),
     }
 
 
@@ -217,7 +218,7 @@ def aggregate_group(
 
         component_scores = {}
         component_counts = {}
-        for component in PUBLIC_COMPONENTS:
+        for component in DISPLAY_COMPONENTS:
             values = [
                 s["components_raw_0to3"][component]
                 for s in scored
@@ -249,7 +250,7 @@ def aggregate_group(
                 "component_counts": component_counts,
             }
         )
-    return sorted(output, key=lambda row: (-(row["overall_9"] or -1), row["display_name"]))
+    return sorted(output, key=lambda row: (-(row["overall_10"] or -1), row["display_name"]))
 
 
 def build_aggregates(records: list[dict[str, Any]], canonical: Any) -> dict[str, Any]:
@@ -312,7 +313,7 @@ def validate(records: list[dict[str, Any]], aggregates: dict[str, Any], canonica
             for key, value in components.items():
                 if value is not None and not 0 <= value <= 3:
                     errors.append(f"out-of-range score {row['sample_id']} {model_id} {key}={value}")
-            expected_9 = mean_present(components, PUBLIC_COMPONENTS)
+            expected_9 = mean_present(components, OVERALL_9_COMPONENTS)
             expected_10 = mean_present(components, list(canonical.COMPONENT_KEYS))
             if abs(score["overall_9_raw"] - expected_9) > 1e-12 or abs(score["overall_10_raw"] - expected_10) > 1e-12:
                 errors.append(f"overall recomputation mismatch for {row['sample_id']} {model_id}")
@@ -364,13 +365,14 @@ def main() -> None:
         },
         "source_commit": source_commit(toolgen_root),
         "scoring": {
+            "primary_metric": "overall_10",
             "source": "augmented_parsed_result_ffjudge_pp.json",
             "scale_raw": [0, 3],
             "scale_public": [0, 100],
             "public_rounding_decimals": 1,
             "overall_10_components": list(canonical.COMPONENT_KEYS),
-            "overall_9_components": PUBLIC_COMPONENTS,
-            "excluded_public_component": EXCLUDED_PUBLIC_COMPONENT,
+            "overall_9_components": OVERALL_9_COMPONENTS,
+            "overall_9_excluded_component": OVERALL_9_EXCLUDED_COMPONENT,
             "missing_policy_default": "zero_fill",
             "missing_policy_exceptions": sorted(canonical.SKIP_MISSING_GENS),
         },

style.css

@@ -116,10 +116,43 @@ h1 {
   font-weight: 500;
   letter-spacing: 0.15em;
   text-transform: uppercase;
-  margin-bottom: 3rem;
+  margin-bottom: 2rem;
   display: block;
 }
 
+.stat-grid {
+  display: grid;
+  grid-template-columns: repeat(4, minmax(0, 1fr));
+  gap: 0.9rem;
+  max-width: 900px;
+  margin: 0 auto 2rem;
+}
+
+.stat-grid article {
+  display: flex;
+  flex-direction: column;
+  padding: 1.15rem 0.75rem;
+  background: var(--glass-bg);
+  border: 1px solid var(--glass-border);
+  border-radius: 16px;
+  box-shadow: 0 12px 30px rgba(15, 23, 42, 0.04);
+}
+
+.stat-grid strong {
+  color: var(--accent-primary);
+  font-size: 1.65rem;
+  line-height: 1.1;
+}
+
+.stat-grid span {
+  margin-top: 0.35rem;
+  color: var(--text-secondary);
+  font-size: 0.78rem;
+  font-weight: 600;
+  letter-spacing: 0.04em;
+  text-transform: uppercase;
+}
+
 .intro-container {
   max-width: var(--max-width);
   margin: 1.5rem auto;
@@ -559,6 +592,20 @@ th.model-column {
   color: var(--accent-primary);
 }
 
+.table-note {
+  max-width: var(--max-width);
+  margin: 1rem auto 0;
+  color: var(--text-secondary);
+  font-size: 0.86rem;
+  text-align: left;
+}
+
+@media (max-width: 720px) {
+  .stat-grid {
+    grid-template-columns: repeat(2, minmax(0, 1fr));
+  }
+}
+
 /* LLM Row Alignment */
 .llm-row {
   display: flex;