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‎content/posts/sourcebench.md‎

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@@ -11,39 +11,40 @@ Most AI benchmarks focus on answer correctness but ignore the quality of cited s
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---
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Author: Yiying Zhang, Reyna Abhyankar, Zijian He
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<head>
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<script src="https://www.google.com/search?q=https://cdn.tailwindcss.com"></script>
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Author: Yiying Zhang, Hexi Jin, Stephen Liu, Yuheng Li, Simran Malik
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<script src="https://www.google.com/search?q=https://cdn.jsdelivr.net/npm/chart.js"></script>
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<link href="https://www.google.com/search?q=https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css" rel="stylesheet">
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<link href="https://www.google.com/search?q=https://fonts.googleapis.com/css2%3Ffamily%3DCrimson%2BPro:ital,wght%400,400%3B0,600%3B0,700%3B1,400%26family%3DInter:wght%40400%3B600%3B700%26display%3Dswap" rel="stylesheet">
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<style>
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body { font-family: 'Crimson Pro', serif; color: #1a1a1a; line-height: 1.6; font-size: 1.25rem; background-color: #ffffff; }
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h1, h2, h3, h4, .sans-serif { font-family: 'Inter', sans-serif; letter-spacing: -0.02em; }
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.caption { font-family: 'Inter', sans-serif; font-size: 0.9rem; color: #666; text-align: center; margin-top: 0.75rem; }
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.insight-block { margin: 2rem 0; padding: 1.5rem; background: #f8fafc; border-left: 4px solid #3b82f6; border-radius: 0 4px 4px 0; }
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.metric-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(300px, 1fr)); gap: 1rem; margin: 2rem 0; }
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.metric-box { border: 1px solid #e2e8f0; border-radius: 8px; padding: 1.25rem; background-color: #fff; transition: transform 0.2s; }
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.metric-box:hover { border-color: #cbd5e1; box-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.05); }
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.metric-tag { font-family: 'Inter', sans-serif; font-size: 0.75rem; text-transform: uppercase; letter-spacing: 0.05em; font-weight: 600; color: #64748b; margin-bottom: 0.5rem; display: block; }
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.heatmap-container { display: grid; grid-template-columns: 30px repeat(8, 1fr); gap: 2px; margin: 2rem 0; font-family: 'Inter', sans-serif; font-size: 0.65rem; }
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.heatmap-label { display: flex; align-items: center; justify-content: center; font-weight: 600; color: #64748b; }
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.heatmap-cell { aspect-ratio: 1; display: flex; align-items: center; justify-content: center; border-radius: 2px; transition: transform 0.1s; font-weight: 500; }
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.grad-neg { background-color: #f1f5f9; color: #94a3b8; } .grad-0 { background-color: #fff1f2; color: #be123c; } .grad-10 { background-color: #ffe4e6; color: #be123c; } .grad-20 { background-color: #fecdd3; color: #be123c; } .grad-30 { background-color: #fda4af; color: #881337; } .grad-40 { background-color: #fb7185; color: #fff; } .grad-50 { background-color: #f43f5e; color: #fff; } .grad-60 { background-color: #e11d48; color: #fff; } .grad-70 { background-color: #be123c; color: #fff; } .grad-80 { background-color: #9f1239; color: #fff; } .grad-90 { background-color: #881337; color: #fff; } .grad-100 { background-color: #4c0519; color: #fff; }
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.heatmap-cell:hover { transform: scale(1.2); z-index: 10; box-shadow: 0 4px 6px -1px rgba(0,0,0,0.2); }
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.intent-card { background: #fff; border: 1px solid #e2e8f0; border-radius: 8px; padding: 1.5rem; margin-bottom: 1rem; }
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.intent-header { display: flex; align-items: center; gap: 0.75rem; margin-bottom: 0.75rem; font-family: 'Inter', sans-serif; font-weight: 700; color: #1e293b; }
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.intent-stat { display: inline-block; padding: 0.25rem 0.5rem; border-radius: 4px; font-size: 0.75rem; font-family: 'Inter', sans-serif; font-weight: 600; margin-right: 0.5rem; }
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.stat-good { background: #dcfce7; color: #166534; } .stat-bad { background: #fee2e2; color: #991b1b; }
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table { width: 100%; border-collapse: separate; border-spacing: 0; font-family: 'Inter', sans-serif; font-size: 0.85rem; margin: 2rem 0; border: 1px solid #e2e8f0; border-radius: 8px; overflow: hidden; }
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th { background-color: #f8fafc; color: #64748b; font-weight: 600; text-transform: uppercase; font-size: 0.75rem; padding: 0.75rem 1rem; text-align: left; border-bottom: 1px solid #e2e8f0; }
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tr:last-child td { border-bottom: none; }
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/* Scoped styles strictly for figures and tables */
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.chart-wrapper { position: relative; height: 350px; width: 100%; border: 1px solid #e2e8f0; border-radius: 8px; padding: 1rem; margin: 2rem 0; background: #fff; box-shadow: 0 1px 3px rgba(0,0,0,0.05); }
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.styled-table { width: 100%; border-collapse: separate; border-spacing: 0; font-family: system-ui, -apple-system, sans-serif; font-size: 0.85rem; margin: 2rem 0; border: 1px solid #e2e8f0; border-radius: 8px; overflow: hidden; }
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.styled-table th { background-color: #f8fafc; color: #64748b; font-weight: 600; text-transform: uppercase; font-size: 0.75rem; padding: 0.75rem 1rem; text-align: left; border-bottom: 1px solid #e2e8f0; }
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.styled-table td { padding: 0.75rem 1rem; border-bottom: 1px solid #f1f5f9; color: #334155; }
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.styled-table tr:last-child td { border-bottom: none; }
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.rank-col { font-weight: 700; color: #94a3b8; width: 60px; }
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.score-col { font-weight: 700; color: #0f172a; text-align: right; }
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.metric-col { color: #64748b; text-align: right; }
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.heatmap-container { display: grid; grid-template-columns: 30px repeat(8, 1fr); gap: 2px; margin: 2rem 0; font-family: system-ui, -apple-system, sans-serif; font-size: 0.65rem; max-width: 600px; }
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.heatmap-label { display: flex; align-items: center; justify-content: center; font-weight: 600; color: #64748b; }
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.heatmap-cell { aspect-ratio: 1; display: flex; align-items: center; justify-content: center; border-radius: 2px; font-weight: 500; color: #fff; }
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.heatmap-cell:hover { opacity: 0.8; }
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.grad-neg { background-color: #f1f5f9; color: #94a3b8; }
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.grad-0 { background-color: #fff1f2; color: #be123c; }
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.grad-10 { background-color: #ffe4e6; color: #be123c; }
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.grad-20 { background-color: #fecdd3; color: #be123c; }
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.grad-30 { background-color: #fda4af; color: #881337; }
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.grad-40 { background-color: #fb7185; }
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.grad-50 { background-color: #f43f5e; }
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.grad-60 { background-color: #e11d48; }
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.grad-70 { background-color: #be123c; }
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.grad-80 { background-color: #9f1239; }
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.grad-100 { background-color: #4c0519; }
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</style>
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</head>
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Large Language Models (LLMs) increasingly answer queries by citing web sources. While web search mitigates hallucinations by grounding responses in external data, it introduces a new dependency: the quality of the sources themselves.
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<tr><td class="rank-col">10</td><td>Tavily</td><td class="score-col">78.3</td><td class="metric-col">3.8</td><td class="metric-col">3.9</td></tr>
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</tbody>
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</table>
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<div class="caption">Table 4: Main Leaderboard. "Content Metric" averages Relevance, Factuality, and Objectivity.</div>
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<div class="caption">Table 1: SourceBench Leaderboard. "Content Metric" averages Relevance, Factuality, and Objectivity.</div>
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## Key Insights
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</div>
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<div class="caption">Figure 4: Full Correlation Matrix. Colors represent correlation strength in 0.1 intervals.</div>
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Conclusion: From Retrieval to Judgment
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## Conclusion: From Retrieval to Judgment
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As AI systems transition from passive tools to active agents, the "black box" of retrieval is no longer acceptable. SourceBench demonstrates that high-parameter reasoning cannot fix low-quality context.
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