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| <html lang="en"> |
| <head> |
| <meta charset="UTF-8"> |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> |
| <title>Repro — Beyond Confidence: Adaptive and Coherent Decoding for DLMs</title> |
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| <style> |
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| @page { size: 60in 36in; margin: 0; } |
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| :root { |
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| --accent: #A61C2B; |
| --accent-deep: #74141E; |
| --accent-light: #F6E8EA; |
| --accent-soft: #EFD6D9; |
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| --gold: #3D4A5C; |
| --gold-soft: #ECEDEF; |
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| --text-primary: #1A1A1A; |
| --text-secondary: #555555; |
| --text-muted: #888888; |
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| --bg-page: #F6F2F0; |
| --bg-card: #FFFFFF; |
| --bg-card-tint: #FAFAFB; |
| --bg-emphasis: var(--accent-light); |
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| --border-soft: #D8D8D8; |
| --border-strong: var(--accent); |
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| --bg-viewport: #2B2B2B; |
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| --u: 1.6px; |
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| --fs-1: calc(9 * var(--u)); |
| --fs-2: calc(10 * var(--u)); |
| --fs-3: calc(11 * var(--u)); |
| --fs-4: calc(12 * var(--u)); |
| --fs-5: calc(13 * var(--u)); |
| --fs-6: calc(15 * var(--u)); |
| --fs-7: calc(16 * var(--u)); |
| --fs-8: calc(22 * var(--u)); |
| --fs-9: calc(32 * var(--u)); |
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| --font-serif: "Charter", "Source Serif Pro", "Georgia", serif; |
| --font-sans: "Inter", "Helvetica Neue", sans-serif; |
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| --shadow-screen: 0 0 60px rgba(0, 0, 0, 0.5); |
| --shadow-card: 0 calc(2 * var(--u)) calc(6 * var(--u)) rgba(45, 95, 139, 0.05); |
| --ornament-ink: rgba(45, 95, 139, 0.06); |
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| } |
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| * { box-sizing: border-box; margin: 0; padding: 0; } |
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| html, body { |
| background: var(--bg-viewport); |
| font-family: var(--font-serif); |
| color: var(--text-primary); |
| -webkit-font-smoothing: antialiased; |
| } |
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| .poster { |
| width: calc(1524 * var(--u)); |
| height: calc(914 * var(--u)); |
| background: var(--bg-page); |
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| background-image: |
| radial-gradient(ellipse at top left, rgba(45, 95, 139, 0.06), transparent 40%), |
| radial-gradient(ellipse at bottom right, rgba(201, 162, 74, 0.05), transparent 50%); |
| margin: 20px auto; |
| padding: calc(10 * var(--u)) calc(14 * var(--u)); |
| display: grid; |
| grid-template-rows: auto auto 1fr auto; |
| gap: calc(6 * var(--u)); |
| box-shadow: var(--shadow-screen); |
| position: relative; |
| overflow: hidden; |
| } |
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| .poster::before { |
| content: ""; |
| position: absolute; top: 0; left: 0; right: 0; |
| height: calc(8 * var(--u)); |
| background: var(--accent); |
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| .header { |
| display: grid; |
| grid-template-columns: 1fr minmax(50%, auto) 1fr; |
| align-items: center; |
| gap: calc(16 * var(--u)); |
| padding: calc(2 * var(--u)) calc(4 * var(--u)) calc(5 * var(--u)); |
| border-bottom: calc(2 * var(--u)) solid var(--accent); |
| } |
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| .venue-badge { |
| justify-self: start; |
| display: flex; flex-direction: column; |
| align-items: center; justify-content: center; |
| min-width: calc(95 * var(--u)); |
| text-align: center; |
| border-right: calc(1 * var(--u)) solid var(--border-soft); |
| padding-right: calc(12 * var(--u)); |
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| font-family: var(--font-sans); |
| font-weight: 800; |
| font-size: var(--fs-9); |
| color: var(--accent-deep); |
| line-height: 1; |
| letter-spacing: -0.5px; |
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| font-family: var(--font-sans); |
| font-size: var(--fs-5); |
| color: var(--text-secondary); |
| margin-top: calc(3 * var(--u)); |
| letter-spacing: 1.2px; |
| } |
| .venue-badge .vb-tag { |
| font-family: var(--font-sans); |
| font-size: var(--fs-2); |
| color: var(--accent); |
| font-weight: 700; |
| margin-top: calc(2 * var(--u)); |
| letter-spacing: 1.2px; |
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| .title-block { text-align: center; min-width: 0; } |
| .title { |
| font-family: var(--font-sans); |
| font-weight: 800; |
| font-size: var(--fs-9); |
| line-height: 1.05; |
| color: var(--accent-deep); |
| letter-spacing: -0.5px; |
| } |
| .title .accent { color: var(--gold); } |
| .subtitle { |
| font-family: var(--font-sans); |
| font-weight: 500; |
| font-size: var(--fs-6); |
| color: var(--text-secondary); |
| margin-top: calc(2 * var(--u)); |
| font-style: italic; |
| } |
| .authors-line { |
| font-family: var(--font-sans); |
| font-size: var(--fs-4); |
| color: var(--accent); |
| font-weight: 600; |
| margin-top: calc(3 * var(--u)); |
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| .authors-line sup { font-size: 0.7em; color: var(--accent); } |
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| color: var(--text-secondary); |
| font-weight: 400; |
| display: block; |
| margin-top: calc(2 * var(--u)); |
| font-size: var(--fs-4); |
| } |
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| .right-block { |
| justify-self: end; |
| display: flex; align-items: center; |
| gap: calc(10 * var(--u)); |
| } |
| .qr-block { display: flex; flex-direction: column; align-items: center; gap: calc(2 * var(--u)); } |
| .qr-block img { |
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| width: calc(65 * var(--u)); |
| height: calc(65 * var(--u)); |
| border: calc(2 * var(--u)) solid var(--accent); |
| border-radius: calc(4 * var(--u)); |
| background: white; |
| padding: calc(2 * var(--u)); |
| } |
| .qr-label { |
| font-family: var(--font-sans); |
| font-size: var(--fs-3); |
| color: var(--accent); |
| font-weight: 600; |
| } |
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| .logo-slot img { height: calc(85 * var(--u)); width: auto; max-width: calc(360 * var(--u)); object-fit: contain; display: block; } |
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| .logo-slot.logo-tall img, |
| .logo-slot.logo-square img { height: calc(85 * var(--u)); } |
| .logo-slot.logo-wide img { height: calc(58 * var(--u)); max-width: calc(300 * var(--u)); } |
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| .logo-chip { |
| display: inline-flex; align-items: center; justify-content: center; |
| background: var(--bg-card); border-radius: calc(3 * var(--u)); |
| padding: calc(3 * var(--u)) calc(5 * var(--u)); |
| } |
| .logo-chip.logo-chip-dark { background: var(--text-primary); } |
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| .logo-row { display: flex; align-items: center; gap: calc(5 * var(--u)); } |
| .logo-row img { height: calc(68 * var(--u)); width: auto; display: block; } |
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| .logo-row .lr-item { |
| display: flex; flex-direction: column; align-items: center; |
| gap: calc(2 * var(--u)); |
| background: var(--bg-card); |
| border: 1px solid var(--border-soft); |
| border-radius: calc(3 * var(--u)); |
| padding: calc(4 * var(--u)) calc(6 * var(--u)); |
| } |
| .logo-row .lr-item img { height: calc(58 * var(--u)); } |
| .logo-row .lr-label { |
| font-family: var(--font-sans); font-weight: 600; font-size: var(--fs-1); |
| color: var(--text-secondary); text-align: center; line-height: 1.15; |
| } |
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| .logo-row.logo-stack { flex-direction: column; align-items: flex-start; gap: calc(8 * var(--u)); } |
| .logo-row.logo-stack img { width: calc(170 * var(--u)); height: auto; } |
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| .venue-badge img { height: calc(62 * var(--u)); width: auto; display: block; margin: 0 auto calc(2 * var(--u)); } |
| .venue-badge .vb-title { font-family: var(--font-sans); font-weight: 800; font-size: var(--fs-5); color: var(--accent-deep); letter-spacing: 0.5px; } |
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| .framework-banner { |
| display: flex; |
| align-items: center; |
| gap: calc(16 * var(--u)); |
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| background: var(--bg-emphasis); |
| border: calc(1 * var(--u)) solid var(--border-soft); |
| border-left: calc(6 * var(--u)) solid var(--accent); |
| border-radius: calc(6 * var(--u)); |
| padding: calc(6 * var(--u)) calc(14 * var(--u)); |
| } |
| .framework-banner img { height: calc(120 * var(--u)); width: auto; display: block; } |
| .framework-banner .banner-stats { |
| flex: 1; |
| display: grid; |
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| grid-template-columns: repeat(4, 1fr); |
| gap: calc(6 * var(--u)); |
| } |
| .framework-banner .bs-item { |
| background: white; |
| border: calc(1 * var(--u)) solid var(--border-soft); |
| border-left: calc(3 * var(--u)) solid var(--accent); |
| border-radius: calc(3 * var(--u)); |
| padding: calc(2 * var(--u)) calc(8 * var(--u)); |
| text-align: center; |
| } |
| .framework-banner .bs-num { |
| font-family: var(--font-sans); |
| font-weight: 800; |
| font-size: var(--fs-8); |
| color: var(--accent); |
| line-height: 1; |
| } |
| .framework-banner .bs-label { |
| font-family: var(--font-sans); |
| font-size: var(--fs-3); |
| color: var(--text-secondary); |
| margin-top: calc(2 * var(--u)); |
| line-height: 1.2; |
| } |
| .framework-banner .fb-text { |
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| flex: 1.4; |
| font-family: var(--font-serif); |
| font-size: var(--fs-6); |
| line-height: 1.5; |
| text-wrap: pretty; |
| text-align: center; |
| } |
| .framework-banner .fb-text strong { color: var(--accent-deep); } |
| .framework-banner .fb-label { |
| display: inline-block; |
| background: var(--accent); |
| color: white; |
| font-family: var(--font-sans); |
| font-size: var(--fs-5); |
| font-weight: 700; |
| padding: calc(2 * var(--u)) calc(8 * var(--u)); |
| border-radius: calc(4 * var(--u)); |
| text-transform: uppercase; |
| letter-spacing: 1px; |
| vertical-align: middle; |
| line-height: 1; |
| position: relative; |
| top: calc(-1 * var(--u)); |
| } |
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| .framework-banner .banner-figure { |
| flex: 0 0 auto; |
| width: min-content; |
| margin: 0; |
| text-align: center; |
| } |
| .framework-banner .banner-figure img { |
| height: calc(120 * var(--u)); |
| width: auto; |
| display: block; |
| margin-inline: auto; |
| } |
| .framework-banner .banner-figure figcaption { |
| width: 100%; |
| margin-top: calc(2 * var(--u)); |
| font-family: var(--font-sans); |
| font-size: var(--fs-2); |
| line-height: 1.2; |
| color: var(--text-secondary); |
| text-align: center; |
| text-wrap: pretty; |
| overflow-wrap: anywhere; |
| } |
| .framework-banner .banner-figure figcaption strong { color: var(--accent-deep); } |
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| .body-grid { |
| display: grid; |
| grid-template-columns: 1fr 1.05fr 1.05fr 1fr; |
| gap: calc(10 * var(--u)); |
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| min-height: 0; |
| } |
| .column { |
| display: flex; flex-direction: column; |
| gap: calc(6 * var(--u)); |
| min-height: 0; |
| height: 100%; |
| padding-bottom: calc(4 * var(--u)); |
| } |
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| .card { |
| background: var(--bg-card); |
| border-radius: calc(5 * var(--u)); |
| padding: calc(4 * var(--u)) calc(9 * var(--u)); |
| border: calc(1 * var(--u)) solid var(--border-soft); |
| box-shadow: var(--shadow-card); |
| position: relative; |
| } |
| .card.tinted { background: var(--bg-card-tint); } |
| .card.card--compact { padding: calc(3 * var(--u)) calc(6 * var(--u)); } |
| .card.highlight { |
| border-left: calc(6 * var(--u)) solid var(--accent); |
| |
| background: var(--bg-emphasis); |
| } |
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| .section-title { |
| font-family: var(--font-sans); |
| font-weight: 700; |
| font-size: var(--fs-7); |
| color: var(--accent-deep); |
| margin-bottom: calc(3 * var(--u)); |
| display: flex; align-items: center; |
| gap: calc(5 * var(--u)); |
| } |
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| .section-title .st-text { flex: 1; min-width: 0; line-height: 1.18; } |
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| |
| .section-title:not(:has(.st-text)) { display: block; line-height: 1.18; } |
| .section-title:not(:has(.st-text)) .num { float: left; margin-right: calc(5 * var(--u)); } |
| .section-title .num { |
| display: inline-flex; align-items: center; justify-content: center; |
| width: calc(22 * var(--u)); height: calc(22 * var(--u)); |
| background: var(--accent); color: white; |
| border-radius: 50%; |
| font-size: var(--fs-5); font-weight: 700; |
| flex-shrink: 0; |
| } |
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| .section-title .key-mark { color: var(--gold); font-size: var(--fs-3); } |
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| .body-text, .card p, .card li { |
| font-family: var(--font-serif); |
| font-size: var(--fs-4); |
| line-height: 1.3; |
| color: var(--text-primary); |
| } |
| .card ul, .card ol { padding-left: calc(18 * var(--u)); } |
| .card li { margin-bottom: calc(2 * var(--u)); } |
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| .keyword { color: var(--accent); font-weight: 700; } |
| .keyword-gold { color: var(--gold); font-weight: 700; } |
| .highlight-text { |
| background: var(--bg-emphasis); |
| padding: 0 calc(3 * var(--u)); |
| border-radius: calc(2 * var(--u)); |
| } |
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| .eqn { |
| background: var(--bg-emphasis); |
| border-left: calc(3 * var(--u)) solid var(--accent); |
| padding: calc(4 * var(--u)) calc(10 * var(--u)); |
| margin: calc(4 * var(--u)) 0; |
| font-size: var(--fs-5); |
| overflow-x: hidden; |
| } |
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| .eqn--large { font-size: calc(var(--fs-5) * 1.25); } |
| .eqn .label { |
| display: block; |
| font-family: var(--font-sans); |
| font-size: var(--fs-2); |
| color: var(--accent); |
| font-weight: 600; |
| margin-bottom: calc(2 * var(--u)); |
| text-transform: uppercase; |
| letter-spacing: 1px; |
| } |
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| .callout { |
| background: var(--accent); |
| color: white; |
| padding: calc(5 * var(--u)) calc(10 * var(--u)); |
| border-radius: calc(4 * var(--u)); |
| font-size: var(--fs-4); |
| margin: calc(4 * var(--u)) 0; |
| } |
| .callout strong { color: var(--gold); } |
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| .callout.gold { |
| background: var(--gold); |
| color: var(--accent-deep); |
| } |
| .callout.gold strong { color: var(--accent-deep); } |
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| .figure { margin: calc(4 * var(--u)) 0; text-align: center; } |
| .figure img:not([class*="w-"]) { width: 100%; } |
| .figure--wide img { width: 100%; } |
| .figure img { |
| border-radius: calc(4 * var(--u)); |
| border: calc(1 * var(--u)) solid var(--border-soft); |
| background: white; |
| } |
| .figure .caption { |
| font-family: var(--font-sans); |
| font-size: var(--fs-3); |
| color: var(--text-secondary); |
| margin-top: calc(3 * var(--u)); |
| line-height: 1.3; |
| text-align: left; |
| } |
| .figure .caption strong { color: var(--accent-deep); } |
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| .fig-wrap::after { content: ""; display: table; clear: both; } |
| .ff-fig { |
| float: right; |
| width: 48%; max-width: 58%; min-width: 38%; |
| margin: calc(1 * var(--u)) 0 calc(3 * var(--u)) calc(11 * var(--u)); |
| text-align: center; |
| } |
| .ff-fig.left { |
| float: left; |
| margin: calc(1 * var(--u)) calc(11 * var(--u)) calc(3 * var(--u)) 0; |
| } |
| .ff-fig img { |
| display: block; |
| width: 100%; |
| border-radius: calc(4 * var(--u)); |
| border: calc(1 * var(--u)) solid var(--border-soft); |
| background: white; |
| } |
| .ff-fig .caption { |
| font-family: var(--font-sans); |
| font-size: var(--fs-3); |
| color: var(--text-secondary); |
| margin-top: calc(3 * var(--u)); |
| line-height: 1.3; |
| text-align: center; |
| } |
| |
| |
| .result-table { |
| width: 100%; |
| border-collapse: collapse; |
| font-family: var(--font-sans); |
| font-size: var(--fs-3); |
| margin-top: calc(3 * var(--u)); |
| } |
| .result-table th, .result-table td { |
| padding: calc(2 * var(--u)) calc(4 * var(--u)); |
| text-align: center; |
| border-bottom: calc(1 * var(--u)) solid var(--border-soft); |
| } |
| .result-table thead th { |
| background: var(--accent); color: white; |
| font-weight: 600; font-size: var(--fs-2); |
| } |
| .result-table tbody tr.group-row td { |
| background: var(--bg-emphasis); font-weight: 700; |
| text-align: left; |
| color: var(--accent-deep); |
| padding-left: calc(8 * var(--u)); |
| border-bottom: calc(2 * var(--u)) solid var(--accent); |
| } |
| .result-table tbody tr.ours td { background: var(--gold-soft); font-weight: 700; } |
| .result-table tbody tr.ours td:first-child { color: var(--accent-deep); } |
| |
| .result-table tbody tr.reference td { color: var(--text-muted); } |
| .result-table .method { text-align: left; padding-left: calc(8 * var(--u)); } |
| .result-table .best { color: var(--accent); font-weight: 700; } |
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| .result-table .num-cell { color: var(--accent-deep); font-weight: 700; } |
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| .keybox { |
| display: grid; |
| grid-template-columns: repeat(3, 1fr); |
| gap: calc(4 * var(--u)); |
| margin: calc(4 * var(--u)) 0 0; |
| } |
| .keybox .kb-item { |
| background: var(--bg-emphasis); |
| border-top: calc(2 * var(--u)) solid var(--accent); |
| padding: calc(3 * var(--u)); |
| text-align: center; |
| |
| |
| |
| display: flex; flex-direction: column; justify-content: center; |
| border-radius: 0 0 calc(3 * var(--u)) calc(3 * var(--u)); |
| } |
| .kb-item .kb-num { |
| font-family: var(--font-sans); |
| font-weight: 800; |
| font-size: var(--fs-6); |
| color: var(--accent); |
| line-height: 1; |
| } |
| .kb-item .kb-label { |
| font-family: var(--font-sans); |
| font-size: var(--fs-1); |
| color: var(--text-secondary); |
| margin-top: calc(2 * var(--u)); |
| line-height: 1.1; |
| } |
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| |
| .takeaways-strip { |
| display: grid; |
| grid-template-columns: auto repeat(4, 1fr); |
| align-items: center; |
| gap: calc(10 * var(--u)); |
| |
| background: var(--bg-emphasis); |
| border: calc(1 * var(--u)) solid var(--border-soft); |
| border-radius: calc(5 * var(--u)); |
| padding: calc(8 * var(--u)) calc(12 * var(--u)); |
| } |
| .takeaways-strip .ts-title { |
| font-family: var(--font-sans); |
| font-size: var(--fs-6); |
| font-weight: 800; |
| color: var(--accent-deep); |
| display: flex; align-items: center; gap: calc(6 * var(--u)); |
| } |
| .takeaways-strip .ts-title .num { |
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| </head> |
| <body> |
|
|
| <div class="poster" data-measure-role="poster"> |
|
|
| |
| <header class="header" data-measure-role="header"> |
| <div class="venue-badge"> |
| <div class="vb-venue">ICML</div> |
| <div class="vb-year">2026</div> |
| <div class="vb-tag">REPRO</div> |
| </div> |
|
|
| <div class="title-block"> |
| <h1 class="title">Beyond Confidence: Adaptive and Coherent Decoding for Diffusion Language Models |
| <span class="accent">[ A Reproduction ]</span></h1> |
| <div class="subtitle">The idea reproduces. The speedup it is packaged with is structurally impossible at the paper's own hyperparameters.</div> |
| <div class="authors-line"> |
| <span class="author">Independent reproduction of ICML 2026 paper #6883 (OpenReview b0O96emqNj · arXiv 2512.02044)</span> |
| <span class="aff">· no official code released — reimplemented from the equations · Dream-7B-Instruct · 1×L40S, ~7 GPU-h, ~$13</span> |
| </div> |
| </div> |
|
|
| <div class="qr-block"> |
| <img src="images/qr_bundle.png" alt="QR code linking to the reproduction bundle on Hugging Face"> |
| <div class="qr-label">code, per-example<br>outputs & job scripts</div> |
| </div> |
| </header> |
|
|
| |
| |
| |
| <section class="framework-banner" data-measure-role="banner"> |
| <div class="fb-text"> |
| <span class="fb-label">Verdict</span> |
| <strong>CCD's quality gain reproduces (+4.69 vs +4.65 claimed). Its advertised 3.48× speedup cannot exist at the stated <span class="keyword">V=4, d=3</span></strong> — a ceiling <strong>k ≤ V/(d+1)</strong>, derived from the paper's own Eqs. (16)–(17), caps decoding at exactly 1 token per step. Widening the buffer to V≈16 buys back the reported speed, and spends the quality gain to do it. The two are each reachable alone, never together. |
| </div> |
| <div class="banner-stats"> |
| <div class="bs-item"><div class="bs-num">+4.69</div><div class="bs-label">CCD on HumanEval<br>(paper: +4.65) ✓</div></div> |
| <div class="bs-item"><div class="bs-num">1.02×</div><div class="bs-label">measured speedup<br>(paper: 3.48×) ✗</div></div> |
| <div class="bs-item"><div class="bs-num">8/8</div><div class="bs-label">configs match the<br>ceiling (1.9% err)</div></div> |
| <div class="bs-item"><div class="bs-num">V≈16</div><div class="bs-label">recovers the paper's<br>numbers, not V=4</div></div> |
| </div> |
| </section> |
|
|
| |
| <div class="body-grid" data-measure-role="body"> |
|
|
| <div class="column" data-measure-role="column"> |
|
|
| <div class="card highlight" data-measure-role="card"> |
| <div class="section-title"><span class="num">1</span><span class="st-text">What was reproduced</span></div> |
| <p class="body-text"> |
| CCD replaces a diffusion LM's <span class="keyword">single-step</span> confidence with a marginal |
| <strong>p̄</strong> averaged over a sliding buffer of the last <em>d</em> iterations, keeping the |
| top-<em>V</em> tokens (Eq. 6/16/17). CCD-DS spends that signal as an |
| <span class="keyword">adaptive unmasking budget</span> (Eq. 20). |
| </p> |
| <p class="body-text mt-3"> |
| <strong>No code was released.</strong> We reimplemented from the equations as a drop-in replacement for |
| Dream's <code>_sample</code>, copying its confidence metric, logit shift and budget schedule verbatim — |
| the arms differ <em>only</em> in which distribution a token is drawn from. |
| </p> |
| </div> |
|
|
| <div class="card" data-measure-role="card"> |
| <div class="section-title"><span class="num">2</span><span class="st-text">The harness is faithful</span></div> |
| <p class="body-text">Three independent baselines land on the paper's numbers — this is what licenses every verdict below.</p> |
| <table class="result-table"> |
| <thead><tr><th>baseline</th><th>paper</th><th>ours</th></tr></thead> |
| <tbody> |
| <tr><td>Trip Plan</td><td>15.10</td><td class="num-cell">15.62</td></tr> |
| <tr><td>HumanEval</td><td>52.66</td><td class="num-cell">53.12</td></tr> |
| <tr><td>Trip City=3</td><td>58</td><td class="num-cell">55.0</td></tr> |
| </tbody> |
| </table> |
| <p class="body-text mt-3 fs-4"> |
| Hyperparameters are Dream's own eval scripts — we tuned nothing. |
| </p> |
| </div> |
|
|
| <div class="card" data-measure-role="card"> |
| <div class="section-title"><span class="num">3</span><span class="st-text">Bonus: Dream's own recipe is broken</span></div> |
| <p class="body-text"> |
| Dream's published HumanEval setting (<span class="keyword">T=0.1, top_p=0.9</span>) emits |
| <strong>768/768 EOS</strong> under Dream's <em>own</em> <code>diffusion_generate</code> — yet this paper |
| and the Dream paper both report <strong>52.66</strong> from it. |
| </p> |
| <p class="body-text mt-3"> |
| <strong>Cause:</strong> T<1 scales logits ×1/T and top_p<1 keeps only the argmax, so negative |
| entropy is <span class="keyword">exactly 0 at 242/256 positions</span> and the ranking ties. Only the |
| <em>conjunction</em> is fatal — we ran HumanEval at T=0. |
| </p> |
| </div> |
|
|
| <div class="card pb-12" data-logbook-target="conclusion" data-measure-role="card"> |
| <div class="section-title"><span class="num">4</span><span class="st-text">Scope, cost & what's next</span></div> |
| <p class="body-text"> |
| <strong>~7 GPU-h on one L40S, ~$13</strong>, against ~250 GPU-h (~$450) to run all of Table 1 at |
| full size — spent on the claims that discriminate. |
| </p> |
| <p class="body-text mt-3"> |
| <strong>Honest limits.</strong> Scores ran at n=64 (Trip, HumanEval), n=40 (ablation), n=16 (temperature) — |
| underpowered, so we report McNemar paired tests, not point estimates, and call Claim 3's score |
| <em>inconclusive</em> rather than refuted. <strong>Next:</strong> full HumanEval (n=164, ~$6) would take |
| CCD's 3–0 to p≈0.008. |
| </p> |
| </div> |
|
|
| </div> |
|
|
| <div class="column" data-measure-role="column"> |
|
|
| <div class="card" data-logbook-target="claim-2-propositions-1-and-2" data-measure-role="card"> |
| <div class="section-title"><span class="num">5</span><span class="st-text">Theory: Prop. 1 ✓, Prop. 2 ✗</span></div> |
| <p class="body-text"> |
| <strong>Prop. 1</strong> — <em>H(x|s) = H(x|c,s) + I(x;c|s)</em> — is a correct identity, exact to |
| <strong>2.2e-15</strong> over 2000 seeded random joints. |
| </p> |
| <p class="body-text mt-3"> |
| <strong>Prop. 2 does not follow.</strong> Lemma 1 is an <em>upper</em> bound; Eq. (12) swaps its RHS for a |
| trajectory-averaged MI that is <span class="keyword">strictly smaller</span> (0.191 vs 0.669 bits in our |
| counterexample) while keeping the ≤. |
| </p> |
| <p class="body-text mt-3"> |
| Worse, its RHS is <strong>sampler-independent</strong> — it depends on the data and the trained model, |
| not on how tokens are picked. The only lever is <em>G/T</em>, so CCD-DS's fewer steps make the bound |
| <strong>~3.4× looser</strong> — the opposite of governing it. |
| </p> |
| </div> |
|
|
| <div class="card highlight" data-measure-role="card"> |
| <div class="section-title"><span class="num">6</span><span class="st-text">A ceiling on the speedup</span></div> |
| <p class="body-text"> |
| Let <em>S<sub>u</sub></em> be the top-<em>V</em> set at step <em>u</em>. Eq. (17) intersects the last |
| <em>d</em>+1 of them; every token decoded in that window came from <em>S<sub>t−d</sub></em> and never |
| returns, which in steady state forces: |
| </p> |
| <div class="eqn eqn--large"> |
| |I<sup>c</sup><sub>t</sub>| ≤ V − Σk ⇒ <strong>k ≤ V/(d+1)</strong> |
| </div> |
| <p class="body-text mt-3"> |
| Speedup <em>is</em> mean tokens/step, so <strong>V/(d+1) caps it</strong>. At the paper's |
| <span class="keyword">V=4, d=3</span>: <strong>4/4 = 1.0×</strong> — no speedup is possible. The cap |
| follows from position bookkeeping alone; no model or benchmark enters. |
| </p> |
| </div> |
|
|
| <div class="card pb-9" data-logbook-target="claim-1-ccd-sliding-window-buffer-approximates-the-marginal" data-measure-role="card"> |
| <div class="section-title"><span class="num">7</span><span class="st-text">Measured: the budget starves</span></div> |
| <figure class="figure"> |
| <img class="w-90" src="images/fig_ic_hist.png" alt="Histogram of intersection size"> |
| <div class="caption">At V=4, d=3 the intersection holds exactly one candidate in 72% of steps — Eq. (20)'s budget has nothing to adapt with.</div> |
| </figure> |
| <p class="body-text mt-3 fs-4"> |
| The stability heuristic — the part the paper describes tuning — passes on <strong>96.1%</strong> of candidates. It is not the bottleneck; the intersection is. |
| </p> |
| </div> |
|
|
| </div> |
|
|
| <div class="column" data-measure-role="column"> |
|
|
| <div class="card" data-measure-role="card"> |
| <div class="section-title"><span class="num">8</span><span class="st-text">The ceiling predicts, 8/8</span></div> |
| <figure class="figure"> |
| <img class="w-80" src="images/fig_k_law.png" alt="Predicted vs measured tokens per step"> |
| <div class="caption">Predicted from the equations before any run, then measured on Dream-7B: mean absolute error 1.9%, worst case 6.7%. Nothing here is fitted.</div> |
| </figure> |
| <p class="body-text mt-3 fs-4"> |
| It holds on the <em>d</em> axis too: d=1→1.95 (predicted 2.00), d=2→1.31 (1.33), d=3→1.01 (1.00). |
| At V=1–2 CCD-DS degenerates <em>exactly</em> to baseline: 256.0 steps, 99.6% fallback, identical score. |
| </p> |
| </div> |
|
|
| <div class="card highlight" data-measure-role="card"> |
| <div class="section-title"><span class="num">9</span><span class="st-text">V≈16 reconciles the paper</span></div> |
| <p class="body-text"> |
| The bound says 3.48× needs <strong>V = 3.48×4 ≈ 14</strong>. We ran V=16 — nothing else changed — |
| and <em>two independent reported quantities</em> reappear: |
| </p> |
| <table class="result-table"> |
| <thead><tr><th></th><th>paper</th><th>V=4</th><th>V=16</th></tr></thead> |
| <tbody> |
| <tr><td>CCD Δ</td><td>+1.83</td><td>−1.56</td><td class="num-cell">+1.56 ✓</td></tr> |
| <tr><td>DS steps</td><td>75.2</td><td>252.1</td><td class="num-cell">70.3 ✓</td></tr> |
| <tr><td>DS speedup</td><td>3.48×</td><td>1.02×</td><td class="num-cell">3.64× ✓</td></tr> |
| </tbody> |
| </table> |
| <p class="body-text mt-3"> |
| On HumanEval too: the bound says 3.04× needs V≥12.2; <strong>V=12 gives 2.89×</strong>. The |
| published <span class="keyword">V=4</span> appears to fit neither benchmark. |
| </p> |
| </div> |
|
|
| <div class="card pb-7" data-logbook-target="claim-3-trip-plan-speedup-and-score-dream-7b" data-measure-role="card"> |
| <div class="section-title"><span class="num">10</span><span class="st-text">Claim 3 — Trip Plan</span></div> |
| <table class="result-table"> |
| <thead><tr><th>arm</th><th>paper</th><th>ours</th><th>speedup</th></tr></thead> |
| <tbody> |
| <tr><td>baseline</td><td>15.10</td><td class="num-cell">15.62</td><td>1.00×</td></tr> |
| <tr><td>+ CCD</td><td>16.93</td><td class="num-cell">14.06</td><td>1.00×</td></tr> |
| <tr><td>+ CCD-DS</td><td>19.01</td><td class="num-cell">14.06</td><td class="num-cell">1.02×</td></tr> |
| <tr class="ours"><td>CCD-DS <em>V=16</em></td><td>—</td><td class="num-cell">12.50</td><td class="num-cell">3.64×</td></tr> |
| </tbody> |
| </table> |
| <p class="body-text mt-3"> |
| <strong>Speedup refuted:</strong> 1.02× vs 3.48× claimed (k=1.015 against the bound's 1.00). |
| The score is <em>inconclusive</em>, not refuted — only <strong>1 of 64</strong> examples changed |
| (McNemar p=1.000), though CCD drove 77% of steps and rewrote 69% of the plans. |
| </p> |
| </div> |
|
|
| </div> |
|
|
| <div class="column" data-measure-role="column"> |
|
|
| <div class="card highlight" data-logbook-target="claim-4-humaneval-ccd-and-ccd-ds-dream-7b" data-measure-role="card"> |
| <div class="section-title"><span class="num">11</span><span class="st-text">Claim 4 — CCD reproduces</span></div> |
| <p class="body-text"> |
| The paper's headline quality claim lands to within <strong>0.04 points</strong>: |
| </p> |
| <table class="result-table"> |
| <thead><tr><th>HumanEval, n=64</th><th>paper</th><th>ours</th></tr></thead> |
| <tbody> |
| <tr><td>baseline</td><td>52.66</td><td class="num-cell">48.44</td></tr> |
| <tr class="ours"><td><strong>+ CCD Δ</strong></td><td><strong>+4.65</strong></td><td class="num-cell"><strong>+4.69</strong> ✓</td></tr> |
| <tr><td>+ CCD-DS speedup</td><td>3.04×</td><td class="num-cell">1.01× ✗</td></tr> |
| </tbody> |
| </table> |
| <p class="body-text mt-3"> |
| Unanimous but underpowered: <strong>3 of 64</strong> improved, none worsened, <em>p=0.250</em>. CCD drove |
| 96% of steps and rewrote 33% of programs. |
| </p> |
| </div> |
|
|
| <div class="card" data-logbook-target="claim-5-historical-buffer-size-ablation" data-measure-role="card"> |
| <div class="section-title"><span class="num">12</span><span class="st-text">Claim 5 — buffer ablation</span></div> |
| <figure class="figure"> |
| <img class="w-80" src="images/fig_ablation_score.png" alt="Accuracy vs buffer width"> |
| <div class="caption">Accuracy falls monotonically and never beats baseline. The paper's 70% peak at size 4; we measure 50.0, under our 52.5 baseline.</div> |
| </figure> |
| <p class="body-text mt-3 fs-4"> |
| The reported "95.54 steps at buffer 4" sits between our V=8 (132.8) and V=16 (68.6) — V≈11 again. |
| </p> |
| </div> |
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| <div class="card pb-8" data-logbook-target="claim-6-temperature-robustness" data-measure-role="card"> |
| <div class="section-title"><span class="num">13</span><span class="st-text">Claim 6 — temperature</span></div> |
| <figure class="figure"> |
| <img class="w-75" src="images/fig_temperature.png" alt="pass@1 vs sampling temperature, baseline vs CCD-DS"> |
| <div class="caption">The gain appears only at T=0 (+6.25 vs +9.8 claimed); at every other temperature CCD-DS is worse or level.</div> |
| </figure> |
| <p class="body-text mt-3 fs-4"> |
| At T=0, <strong>50.0 vs 43.75</strong>. <strong>Caveat:</strong> n=16, and T=0.1/0.4/0.7 sit inside the |
| collapse regime — our weakest test. |
| </p> |
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| <div class="footer" data-measure-role="footer"> |
| <div> |
| <strong class="method-name">Coherent Contextual Decoding (CCD)</strong> · ICML 2026 #6883 · arXiv 2512.02044 · |
| Reproduction bundle, all per-example outputs and the exact job scripts: huggingface.co/datasets/ashishk1331/ccd-repro-code |
| </div> |
| <div> |
| Logbook (every run, figure and per-example output): <span class="repo">huggingface.co/spaces/ashishk1331/ccd-repro-logbook</span> |
| </div> |
| </div> |
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