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</head>
<body>
<header>
<div class="brand">
<a href="./index.html" class="brand-mark">nullspan</a>
<span class="badge" style="background: var(--accent-span);">NullspanBench v3.2 · JevBench Methodology</span>
<span class="badge" id="draw-badge">S+P (500 Scored Observations)</span>
</div>
<nav class="links">
<a href="./index.html">← Interactive Playground</a>
<a href="./bench.html" class="active">Benchmark Leaderboard</a>
<a href="https://huggingface.co/spaces/gnumanth/nullspan" target="_blank" rel="noopener">HF Space</a>
<a href="https://huggingface.co/gnumanth/nullspan" target="_blank" rel="noopener">HF Model (ONNX + PyTorch)</a>
<a href="https://github.com/hemanth/nullspan" target="_blank" rel="noopener">GitHub</a>
</nav>
</header>
<main>
<section class="hero">
<div>
<h1>NullspanBench — Decision & Extraction Model Leaderboard</h1>
<p>
Following the <strong>Benchmark Heaven (JevBench)</strong> evaluation protocol: comparing 19 systems across <strong>Intelligence (I)</strong>, <strong>Probability Calibration (C)</strong>, <strong>Speed (S)</strong>, and <strong>Cost (K)</strong> over <strong>500 zero-leakage observations (S+P)</strong> spanning Open structured extraction (<em>n=336</em>) and Sealed Stanford SQuAD v2.0 (<em>n=60</em>), Multi-Numeric Legal/Commercial Contracts (<em>n=96</em>), and Adversarial prompt-injection traps (<em>n=8</em>).
</p>
</div>
<div class="btn-group">
<span class="btn-label">Pool Filter:</span>
<button class="ctrl-btn" id="btn-pool-open" type="button">Open Weights Only</button>
<button class="ctrl-btn active" id="btn-pool-all" type="button">Show All Mixed (+ API Models)</button>
</div>
</section>
<!-- 0. External Public Benchmarks Banner -->
<section class="section-card">
<div class="section-header">
<span>Official External Public Benchmarks · NVIDIA L4 GPU · Zero Test Contamination</span>
<span>Typed Decisions · JevBench · SQuAD v2.0</span>
</div>
<div class="section-body" style="padding: 14px 18px;">
<div class="table-wrap">
<table class="lb-table">
<thead>
<tr>
<th>External Leaderboard</th>
<th>Evaluated Split</th>
<th>Headline Score</th>
<th>Calibration & Schema Validity</th>
<th>Latency & Cost (L4 GPU)</th>
<th>Public Rank / Notes</th>
</tr>
</thead>
<tbody>
<tr style="background: #FBFAF7;">
<td><strong><a href="https://huggingface.co/datasets/LocalLLaMA/typed-decisions" target="_blank" rel="noopener" style="color: var(--ink);">LocalLLaMA/typed-decisions</a></strong></td>
<td>Official <code>test</code> (400 cases · 2,000 decisions)</td>
<td><strong>79.00% Accuracy</strong> (noul 84.2%, choice 76.8%, score 76.8%)</td>
<td>KL <strong>0.0760 (#2)</strong> · Brier <strong>0.0420 (#1 tied)</strong> · ECE <strong>0.1665</strong></td>
<td><strong>9.56 ms/dec</strong> (47.8 ms/case) · 0 output tokens</td>
<td>Specialist (general + <code>train</code>) · <strong>#1 Hub widget · 96.3% of Bayes ceiling</strong></td>
</tr>
<tr>
<td><strong><a href="https://github.com/fstandhartinger/jevbench" target="_blank" rel="noopener" style="color: var(--ink);">Benchmark Heaven / fstandhartinger/jevbench</a></strong></td>
<td>Public Suite (231 items via <code>/v1/systemone</code>)</td>
<td><strong>100.0% Easy (48/48)</strong> · <strong>68.06% Original</strong> · 36.04% Hard</td>
<td><strong>100.0% Strict Valid</strong> · ECE <strong>0.0755</strong> · v1.3 Geo <strong>46.27</strong></td>
<td><strong>38.82 ms p50</strong> · <strong>$0.00604 / 1k</strong></td>
<td>100% fact & tool_selection · 91.7% intent & ordinal</td>
</tr>
<tr style="background: #FBFAF7;">
<td><strong><a href="https://huggingface.co/datasets/rajpurkar/squad_v2" target="_blank" rel="noopener" style="color: var(--ink);">Stanford rajpurkar/squad_v2</a></strong></td>
<td>Zero-Overlap <code>validation</code> (500 items)</td>
<td><strong>87.80% Exact Match · 90.90% F1</strong></td>
<td>HasAns F1 <strong>90.61%</strong> · NoAns EM <strong>91.20%</strong></td>
<td><strong>10.30 ms p50</strong> · <strong>$0.0017 / 1k</strong></td>
<td>NullspanForExtraction 345.3M + <code>qa_null_head</code></td>
</tr>
</tbody>
</table>
</div>
</div>
</section>
<!-- 1. Capability Score Headline Chart -->
<section class="section-card">
<div class="section-header">
<span>1. NullspanBench Capability Score · Mean of Intelligence (I) & Calibration (C)</span>
<span>95% Bootstrap CIs (B=1,000) · S+P Pool</span>
</div>
<div class="section-body">
<div id="capability-bars"></div>
</div>
</section>
<!-- 2. Pareto Frontier: Capability vs Cost & Speed -->
<section class="section-card">
<div class="section-header">
<span>2. Pareto Frontier: Capability Against Cost & Speed</span>
<span>Upper-Right is Best (More Capable & Cheaper / Faster)</span>
</div>
<div class="section-body">
<div class="pareto-grid">
<div class="chart-box">
<h3>Capability vs Cost ($ / 1,000 Decisions · Log Scale)</h3>
<p>Encoders generate <code>0</code> output tokens; autoregressive API decoders pay per generated JSON token.</p>
<div id="pareto-cost-svg"></div>
</div>
<div class="chart-box">
<h3>Capability vs Speed (p50 Latency ms / Decision · Log Scale)</h3>
<p>Bubble size follows the official Composite Score; dashed line traces the Pareto-optimal frontier.</p>
<div id="pareto-speed-svg"></div>
</div>
</div>
</div>
</section>
<!-- 3. Composite Score Leaderboard Table -->
<section class="section-card">
<div class="section-header">
<span>3. Composite Score Leaderboard · Four Axes (0–100) Weighted Harmonic Mean</span>
<span id="ranked-count-label">19 Ranked Systems</span>
</div>
<div class="section-body">
<div class="filter-bar" style="margin-bottom: 12px;">
<div class="btn-group" id="weight-preset-btns">
<span class="btn-label">Weights:</span>
<button class="ctrl-btn active" data-weights="25,25,25,25" type="button">Official 25:25:25:25</button>
<button class="ctrl-btn" data-weights="40,20,20,20" type="button">Option B 40:20:20:20</button>
<button class="ctrl-btn" data-weights="33,33,34,0" type="button">Balanced 33:33:33</button>
<button class="ctrl-btn" data-weights="60,20,10,10" type="button">Accuracy 60:20:10:10</button>
<button class="ctrl-btn" data-weights="20,20,20,40" type="button">Cost 20:20:20:40</button>
<button class="ctrl-btn" data-weights="20,20,40,20" type="button">Speed 20:20:40:20</button>
<button class="ctrl-btn" data-weights="50,50,0,0" type="button">Capability Only</button>
<button class="ctrl-btn" data-weights="100,0,0,0" type="button">Intelligence Only</button>
</div>
<div class="btn-group">
<input type="text" id="search-input" class="search-input" placeholder="Search system or base model..." />
</div>
</div>
<div class="sliders-grid">
<div class="slider-item">
<span>Intelligence (I): <strong id="lbl-w-i">25%</strong></span>
<input type="range" id="sl-w-i" min="0" max="100" value="25" />
</div>
<div class="slider-item">
<span>Calibration (C): <strong id="lbl-w-c">25%</strong></span>
<input type="range" id="sl-w-c" min="0" max="100" value="25" />
</div>
<div class="slider-item">
<span>Speed (S): <strong id="lbl-w-s">25%</strong></span>
<input type="range" id="sl-w-s" min="0" max="100" value="25" />
</div>
<div class="slider-item">
<span>Cost (K): <strong id="lbl-w-k">25%</strong></span>
<input type="range" id="sl-w-k" min="0" max="100" value="25" />
</div>
</div>
<div class="table-wrap">
<table class="lb-table" id="lb-table">
<thead>
<tr>
<th data-sort="rank"># ▲</th>
<th data-sort="name">System ↕</th>
<th data-sort="system_type">Architecture / Runtime ↕</th>
<th data-sort="composite">Composite ↕</th>
<th data-sort="capability">Cap. ↕</th>
<th data-sort="intelligence">Intel. (I) ↕</th>
<th data-sort="calibration">Calib. (C) ↕</th>
<th data-sort="speed">Speed (S) ↕</th>
<th data-sort="cost">Cost (K) ↕</th>
<th data-sort="usd">$/1k dec. ↕</th>
<th data-sort="p50">p50 ms ↕</th>
<th data-sort="ece">Null ECE ↕</th>
<th data-sort="open_set">Open (S) ↕</th>
<th data-sort="sealed_set">Sealed (P) ↕</th>
</tr>
</thead>
<tbody id="lb-tbody"></tbody>
</table>
</div>
</div>
</section>
<!-- 4. Compare Two Systems (4 SVG Radars) -->
<section class="section-card">
<div class="section-header">
<span>4. Compare Two Systems · Multi-Axis Radar Diagnostics</span>
<span>Four Axes · Request Types · Difficulty Tiers · Subject Domains</span>
</div>
<div class="section-body">
<div class="filter-bar">
<div class="btn-group">
<span class="btn-label" style="color: var(--sys-a);">■ System A:</span>
<select id="select-sys-a" class="sys-select"></select>
</div>
<div class="btn-group">
<span class="btn-label" style="color: var(--sys-b);">● System B:</span>
<select id="select-sys-b" class="sys-select"></select>
</div>
</div>
<div class="radar-grid">
<div class="chart-box">
<h3>The Four Score Axes (0–100)</h3>
<p id="radar-desc-axes"></p>
<div id="radar-axes-svg"></div>
</div>
<div class="chart-box">
<h3>Competence per Request Type (Open / Sealed)</h3>
<p id="radar-desc-req"></p>
<div id="radar-req-svg"></div>
</div>
<div class="chart-box">
<h3>Competence per Difficulty Tier (Open & Sealed)</h3>
<p id="radar-desc-tier"></p>
<div id="radar-tier-svg"></div>
</div>
<div class="chart-box">
<h3>Competence by Subject Domain / Use Case</h3>
<p id="radar-desc-domain"></p>
<div id="radar-domain-svg"></div>
</div>
</div>
</div>
</section>
<!-- 5. Competence Heatmap Matrix -->
<section class="section-card">
<div class="section-header">
<span>5. Competence Heatmap by Request Type, Difficulty Tier & Subject Domain</span>
<span>Greener = Stronger Within Column · Exact Observation Counts (n=500)</span>
</div>
<div class="section-body">
<div class="table-wrap">
<table class="lb-table" id="heatmap-table">
<thead>
<tr>
<th>System</th>
<th>Span (Open)</th>
<th>Span (Sealed)</th>
<th>Noul / p_null (Open)</th>
<th>Noul / p_null (Sealed)</th>
<th>Choice (Bool/Enum)</th>
<th>Math & Invariants</th>
<th>Score (Quantiles)</th>
<th>Tier: Easy</th>
<th>Tier: Standard</th>
<th>Tier: Judge</th>
<th>Tier: Hard</th>
<th>SRE Incident</th>
<th>Cloud Invoice</th>
<th>SQuAD v2.0 QA</th>
<th>Contracts (96)</th>
<th>Adversarial</th>
</tr>
</thead>
<tbody id="heatmap-tbody"></tbody>
</table>
</div>
</div>
</section>
</main>
<script>
let BENCH_DATA = null;
let showApiModels = true;
let currentSortKey = 'composite';
let currentSortAsc = false;
let weights = { i: 25, c: 25, s: 25, k: 25 };
function computeWeightedComposite(sys, w) {
const ax = sys.axes;
const wi = w.i, wc = w.c, ws = w.s, wk = w.k;
const wSum = wi + wc + ws + wk;
if (wSum <= 0) return 0;
const denom = (wi / Math.max(1, ax.intelligence)) +
(wc / Math.max(1, ax.calibration)) +
(ws / Math.max(1, ax.speed)) +
(wk / Math.max(1, ax.cost));
return Number((wSum / denom).toFixed(1));
}
function heatColor(score) {
if (score === undefined || score === null) return '#F3F0E8';
const norm = Math.max(0, Math.min(1, (score - 20) / 80));
if (norm >= 0.85) return '#C8F0D4';
if (norm >= 0.60) return '#E2F5D8';
if (norm >= 0.35) return '#FFE484';
return '#F5D0CE';
}
function getFilteredSystems() {
if (!BENCH_DATA) return [];
const q = (document.getElementById('search-input').value || '').toLowerCase().trim();
const list = BENCH_DATA.systems
.filter(s => showApiModels || s.open_weights)
.filter(s => !q || s.name.toLowerCase().includes(q) || s.base_model.toLowerCase().includes(q) || s.system_type.toLowerCase().includes(q))
.map(s => ({
...s,
live_composite: computeWeightedComposite(s, weights)
}));
list.sort((a, b) => {
let va, vb;
switch (currentSortKey) {
case 'name': va = a.name; vb = b.name; break;
case 'system_type': va = a.system_type; vb = b.system_type; break;
case 'composite': va = a.live_composite; vb = b.live_composite; break;
case 'capability': va = a.capability_score; vb = b.capability_score; break;
case 'intelligence': va = a.axes.intelligence; vb = b.axes.intelligence; break;
case 'calibration': va = a.axes.calibration; vb = b.axes.calibration; break;
case 'speed': va = a.axes.speed; vb = b.axes.speed; break;
case 'cost': va = a.axes.cost; vb = b.axes.cost; break;
case 'usd': va = a.usd_per_1k_decisions; vb = b.usd_per_1k_decisions; break;
case 'p50': va = a.latency.p50_ms; vb = b.latency.p50_ms; break;
case 'ece': va = a.calibration_details.null_ece; vb = b.calibration_details.null_ece; break;
case 'open_set': va = a.open_set_score; vb = b.open_set_score; break;
case 'sealed_set': va = a.sealed_set_score; vb = b.sealed_set_score; break;
default: va = a.live_composite; vb = b.live_composite;
}
if (typeof va === 'string') {
return currentSortAsc ? va.localeCompare(vb) : vb.localeCompare(va);
}
return currentSortAsc ? (va - vb) : (vb - va);
});
return list;
}
function renderCapabilityBars(systems) {
const byCap = [...systems].sort((a, b) => b.capability_score - a.capability_score);
const container = document.getElementById('capability-bars');
container.innerHTML = byCap.map((s, idx) => {
const fillBg = s.id.startsWith('nullspan') ? 'var(--accent-span)' : (s.open_weights ? 'var(--accent-list)' : 'var(--accent-null)');
const ci = s.axes.intelligence_ci95 || [s.axes.intelligence, s.axes.intelligence];
return `
<div class="cap-row">
<div class="cap-name">
<div>#${idx + 1} ${s.name}</div>
<span>${s.system_type} · ${s.footprint_mb !== null ? s.footprint_mb + ' MB' : 'Cloud API'}</span>
</div>
<div class="cap-track">
<div class="cap-fill" style="width: ${Math.max(8, s.capability_score)}%; background: ${fillBg};">
I: ${s.axes.intelligence.toFixed(1)} [${ci[0]}, ${ci[1]}] · C: ${s.axes.calibration.toFixed(1)}
</div>
</div>
<div class="cap-score-val">${s.capability_score.toFixed(1)} / 100</div>
</div>
`;
}).join('');
}
function renderParetoChart(systems, containerId, mode) {
const W = 580, H = 300, padL = 52, padR = 28, padT = 24, padB = 42;
const plotW = W - padL - padR, plotH = H - padT - padB;
// X axis: log10(cost) or log10(p50_ms), inverted so right = cheaper / faster!
const xs = systems.map(s => mode === 'cost' ? Math.log10(Math.max(0.00005, s.usd_per_1k_decisions)) : Math.log10(Math.max(0.005, s.latency.p50_ms)));
const minX = Math.min(...xs) - 0.25;
const maxX = Math.max(...xs) + 0.25;
const minY = 30, maxY = 102;
function toX(val) {
// Right is better (smaller cost or smaller latency -> further right)
return padL + ((maxX - val) / Math.max(1e-6, maxX - minX)) * plotW;
}
function toY(cap) {
return padT + ((maxY - cap) / (maxY - minY)) * plotH;
}
const pts = systems.map((s, i) => ({
s,
x: toX(xs[i]),
y: toY(s.capability_score),
r: Math.max(5, Math.min(12, (s.live_composite - 40) / 5))
}));
// Compute Pareto frontier (sorted left-to-right by x, keeping increasing max capability)
const sortedByX = [...pts].sort((a, b) => b.x - a.x);
const frontier = [];
let bestCap = -1;
for (const p of sortedByX) {
if (p.s.capability_score >= bestCap) {
frontier.push(p);
bestCap = p.s.capability_score;
}
}
const frontierPath = frontier.map((p, i) => `${i === 0 ? 'M' : 'L'}${p.x.toFixed(1)},${p.y.toFixed(1)}`).join(' ');
const gridLines = [40, 60, 80, 100].map(yVal => {
const y = toY(yVal);
return `<line x1="${padL}" y1="${y}" x2="${W - padR}" y2="${y}" stroke="#E5E1D8" stroke-dasharray="3,3" />
<text x="${padL - 8}" y="${y + 4}" text-anchor="end" font-family="IBM Plex Mono, monospace" font-size="10" fill="#52504A">${yVal}</text>`;
}).join('');
const circles = pts.map(p => {
const fill = p.s.id.startsWith('nullspan') ? '#FFE484' : (p.s.open_weights ? '#C8F0D4' : '#F5D0CE');
const shortLbl = p.s.name.split(' ')[0];
return `
<g>
<circle cx="${p.x.toFixed(1)}" cy="${p.y.toFixed(1)}" r="${p.r.toFixed(1)}" fill="${fill}" stroke="#111111" stroke-width="1.6">
<title>${p.s.name} · Cap: ${p.s.capability_score} · $/1k: $${p.s.usd_per_1k_decisions} · p50: ${p.s.latency.p50_ms}ms</title>
</circle>
<text x="${(p.x + 8).toFixed(1)}" y="${(p.y + 3).toFixed(1)}" font-family="IBM Plex Mono, monospace" font-size="9.5" font-weight="700" fill="#111111">${shortLbl}</text>
</g>
`;
}).join('');
const xAxisLabel = mode === 'cost' ? 'Cheaper ($/1k decisions, log scale) →' : 'Faster (p50 ms/decision, log scale) →';
document.getElementById(containerId).innerHTML = `
<svg viewBox="0 0 ${W} ${H}" style="width: 100%; height: auto; display: block;">
${gridLines}
<line x1="${padL}" y1="${H - padB}" x2="${W - padR}" y2="${H - padB}" stroke="#111111" stroke-width="1.5" />
<line x1="${padL}" y1="${padT}" x2="${padL}" y2="${H - padB}" stroke="#111111" stroke-width="1.5" />
<path d="${frontierPath}" fill="none" stroke="#111111" stroke-width="1.8" stroke-dasharray="5,4" />
${circles}
<text x="${W / 2}" y="${H - 10}" text-anchor="middle" font-family="IBM Plex Mono, monospace" font-size="11" font-weight="700" fill="#111111">${xAxisLabel}</text>
<text x="14" y="${H / 2}" text-anchor="middle" transform="rotate(-90 14 ${H / 2})" font-family="IBM Plex Mono, monospace" font-size="11" font-weight="700" fill="#111111">Capability Score</text>
</svg>
`;
}
function renderLeaderboardTable(systems) {
document.getElementById('ranked-count-label').textContent = `${systems.length} Ranked Systems`;
const tbody = document.getElementById('lb-tbody');
tbody.innerHTML = systems.map((s, idx) => {
const ax = s.axes;
return `
<tr>
<td><strong>${idx + 1}</strong></td>
<td>
<strong>${s.name}</strong><br/>
<span style="font-size: 0.68rem; color: var(--ink-muted);">${s.base_model}</span>
</td>
<td>${s.system_type}</td>
<td><span class="axis-pill" style="background: var(--accent-span); font-size: 0.85rem;">${s.live_composite.toFixed(1)}</span></td>
<td><strong>${s.capability_score.toFixed(1)}</strong></td>
<td style="background: ${heatColor(ax.intelligence)}">${ax.intelligence.toFixed(1)}</td>
<td style="background: ${heatColor(ax.calibration)}">${ax.calibration.toFixed(1)}</td>
<td style="background: ${heatColor(ax.speed)}">${ax.speed.toFixed(1)}</td>
<td style="background: ${heatColor(ax.cost)}">${ax.cost.toFixed(1)}</td>
<td>$${s.usd_per_1k_decisions.toFixed(4)}</td>
<td>${s.latency.p50_ms.toFixed(3)} ms</td>
<td>${s.calibration_details.null_ece.toFixed(5)}</td>
<td>${s.open_set_score.toFixed(1)}%</td>
<td><strong>${s.sealed_set_score.toFixed(1)}%</strong></td>
</tr>
`;
}).join('');
}
function drawRadarSvg(containerId, labels, valsA, valsB) {
const W = 380, H = 285, cx = 190, cy = 145, R = 98;
const N = labels.length;
const rings = [25, 50, 75, 100];
function pt(idx, val) {
const angle = -Math.PI / 2 + (idx * 2 * Math.PI) / N;
const r = (Math.max(0, Math.min(100, val)) / 100) * R;
return [cx + r * Math.cos(angle), cy + r * Math.sin(angle)];
}
const ringPolys = rings.map(rk => {
const pts = labels.map((_, i) => pt(i, rk).map(v => v.toFixed(1)).join(',')).join(' ');
return `<polygon points="${pts}" fill="none" stroke="${rk === 50 ? '#111111' : '#D5D0C5'}" stroke-width="${rk === 50 ? '1.2' : '0.8'}" stroke-dasharray="${rk === 50 ? 'none' : '2,2'}" />`;
}).join('');
const spokes = labels.map((lbl, i) => {
const [x, y] = pt(i, 100);
const [lx, ly] = pt(i, 120);
return `
<line x1="${cx}" y1="${cy}" x2="${x.toFixed(1)}" y2="${y.toFixed(1)}" stroke="#D5D0C5" stroke-width="0.9" />
<text x="${lx.toFixed(1)}" y="${(ly + 3).toFixed(1)}" text-anchor="middle" font-family="IBM Plex Mono, monospace" font-size="9.5" font-weight="700" fill="#111111">${lbl}</text>
`;
}).join('');
const polyA = labels.map((_, i) => pt(i, valsA[i]).map(v => v.toFixed(1)).join(',')).join(' ');
const polyB = labels.map((_, i) => pt(i, valsB[i]).map(v => v.toFixed(1)).join(',')).join(' ');
const dotsA = valsA.map((v, i) => {
const [x, y] = pt(i, v);
return `<circle cx="${x.toFixed(1)}" cy="${y.toFixed(1)}" r="3.5" fill="#111111" />`;
}).join('');
const dotsB = valsB.map((v, i) => {
const [x, y] = pt(i, v);
return `<circle cx="${x.toFixed(1)}" cy="${y.toFixed(1)}" r="3.5" fill="#D94E34" />`;
}).join('');
document.getElementById(containerId).innerHTML = `
<svg viewBox="0 0 ${W} ${H}" style="width: 100%; height: auto; display: block;">
${ringPolys}
${spokes}
<polygon points="${polyB}" fill="rgba(217, 78, 52, 0.16)" stroke="#D94E34" stroke-width="2" />
<polygon points="${polyA}" fill="rgba(17, 17, 17, 0.16)" stroke="#111111" stroke-width="2.2" />
${dotsB}
${dotsA}
</svg>
`;
}
function renderComparisonRadars() {
if (!BENCH_DATA) return;
const idA = document.getElementById('select-sys-a').value;
const idB = document.getElementById('select-sys-b').value;
const sysA = BENCH_DATA.systems.find(s => s.id === idA) || BENCH_DATA.systems[0];
const sysB = BENCH_DATA.systems.find(s => s.id === idB) || BENCH_DATA.systems[1];
// 1. Four Axes
const axesLabels = ['Intelligence', 'Calibration', 'Speed', 'Cost'];
const axesA = [sysA.axes.intelligence, sysA.axes.calibration, sysA.axes.speed, sysA.axes.cost];
const axesB = [sysB.axes.intelligence, sysB.axes.calibration, sysB.axes.speed, sysB.axes.cost];
document.getElementById('radar-desc-axes').textContent =
`${sysA.name} vs ${sysB.name} · Intel: ${axesA[0]} vs ${axesB[0]} · Calib: ${axesA[1]} vs ${axesB[1]} · Speed: ${axesA[2]} vs ${axesB[2]} · Cost: ${axesA[3]} vs ${axesB[3]}`;
drawRadarSvg('radar-axes-svg', axesLabels, axesA, axesB);
// 2. Request Types
const reqKeys = [
['span_open', 'Span·Open'],
['span_sealed', 'Span·Sealed'],
['noul_open', 'Noul·Open'],
['noul_sealed', 'Noul·Sealed'],
['choice', 'Choice'],
['math', 'Math/Inv'],
['score', 'Score (p10-90)']
];
const reqA = reqKeys.map(([k]) => sysA.by_request_type[k]?.score ?? 0);
const reqB = reqKeys.map(([k]) => sysB.by_request_type[k]?.score ?? 0);
document.getElementById('radar-desc-req').textContent =
`Noul (Sealed): ${reqA[3]}% vs ${reqB[3]}% · Span (Sealed): ${reqA[1]}% vs ${reqB[1]}% · Math/Invariants: ${reqA[5]}% vs ${reqB[5]}%`;
drawRadarSvg('radar-req-svg', reqKeys.map(x => x[1]), reqA, reqB);
// 3. Difficulty Tiers
const tierKeys = [
['Easy', 'open', 'Easy·Open'],
['Standard', 'open', 'Std·Open'],
['Judge', 'open', 'Judge·Open'],
['Standard', 'sealed', 'Std·Sealed'],
['Hard', 'sealed', 'Hard·Sealed']
];
const tierA = tierKeys.map(([t, p]) => (p === 'open' ? sysA.by_tier_open[t]?.score : sysA.by_tier_sealed[t]?.score) ?? 0);
const tierB = tierKeys.map(([t, p]) => (p === 'open' ? sysB.by_tier_open[t]?.score : sysB.by_tier_sealed[t]?.score) ?? 0);
document.getElementById('radar-desc-tier').textContent =
`Judge (Cross-Field Math): ${tierA[2]}% vs ${tierB[2]}% · Hard (Adversarial + SQuAD Null): ${tierA[4]}% vs ${tierB[4]}%`;
drawRadarSvg('radar-tier-svg', tierKeys.map(x => x[2]), tierA, tierB);
// 4. Subject Domains
const domKeys = [
['incident_report', 'SRE Incident'],
['compute_ledger', 'Cloud Ledger'],
['cluster_throughput_comps', 'Cluster Comps'],
['edge_traffic_forecast', 'Edge Forecast'],
['squad_v2_open_qa', 'SQuAD v2.0'],
['contract_extraction', 'Contracts'],
['adversarial_stress', 'Adversarial']
];
const domA = domKeys.map(([k]) => sysA.by_domain[k]?.score ?? 0);
const domB = domKeys.map(([k]) => sysB.by_domain[k]?.score ?? 0);
document.getElementById('radar-desc-domain').textContent =
`SQuAD v2.0: ${domA[4]}% vs ${domB[4]}% · Contracts (n=96): ${domA[5]}% vs ${domB[5]}% · Adversarial: ${domA[6]}% vs ${domB[6]}%`;
drawRadarSvg('radar-domain-svg', domKeys.map(x => x[1]), domA, domB);
}
function renderHeatmapTable(systems) {
const tbody = document.getElementById('heatmap-tbody');
function cell(obj) {
if (!obj) return `<td class="bh-heat">—</td>`;
return `<td class="bh-heat" style="background: ${heatColor(obj.score)}" title="n=${obj.n} scored observations">${obj.score.toFixed(0)}</td>`;
}
tbody.innerHTML = systems.map(s => `
<tr>
<td><strong>${s.name}</strong></td>
${cell(s.by_request_type.span_open)}
${cell(s.by_request_type.span_sealed)}
${cell(s.by_request_type.noul_open)}
${cell(s.by_request_type.noul_sealed)}
${cell(s.by_request_type.choice)}
${cell(s.by_request_type.math)}
${cell(s.by_request_type.score)}
${cell(s.by_tier_open.Easy)}
${cell(s.by_tier_open.Standard)}
${cell(s.by_tier_open.Judge)}
${cell(s.by_tier_sealed.Hard)}
${cell(s.by_domain.incident_report)}
${cell(s.by_domain.compute_ledger)}
${cell(s.by_domain.squad_v2_open_qa)}
${cell(s.by_domain.contract_extraction)}
${cell(s.by_domain.adversarial_stress)}
</tr>
`).join('');
}
function refreshAll() {
const systems = getFilteredSystems();
renderCapabilityBars(systems);
renderParetoChart(systems, 'pareto-cost-svg', 'cost');
renderParetoChart(systems, 'pareto-speed-svg', 'speed');
renderLeaderboardTable(systems);
renderHeatmapTable(systems);
renderComparisonRadars();
}
async function init() {
const res = await fetch('./bench-data.json');
BENCH_DATA = await res.json();
document.getElementById('draw-badge').textContent =
`${BENCH_DATA.draw_id} · ${BENCH_DATA.n_total_observations} Scored Observations`;
const selA = document.getElementById('select-sys-a');
const selB = document.getElementById('select-sys-b');
selA.innerHTML = BENCH_DATA.systems.map(s => `<option value="${s.id}">${s.name}</option>`).join('');
selB.innerHTML = BENCH_DATA.systems.map(s => `<option value="${s.id}">${s.name}</option>`).join('');
selA.value = 'nullspan-onnx-int8';
selB.value = 'cloudflare-clairic-clef-live';
selA.addEventListener('change', renderComparisonRadars);
selB.addEventListener('change', renderComparisonRadars);
document.getElementById('btn-pool-open').addEventListener('click', () => {
showApiModels = false;
document.getElementById('btn-pool-open').classList.add('active');
document.getElementById('btn-pool-all').classList.remove('active');
refreshAll();
});
document.getElementById('btn-pool-all').addEventListener('click', () => {
showApiModels = true;
document.getElementById('btn-pool-all').classList.add('active');
document.getElementById('btn-pool-open').classList.remove('active');
refreshAll();
});
document.getElementById('weight-preset-btns').addEventListener('click', (e) => {
const btn = e.target.closest('button[data-weights]');
if (!btn) return;
document.querySelectorAll('#weight-preset-btns button').forEach(b => b.classList.remove('active'));
btn.classList.add('active');
const [wi, wc, ws, wk] = btn.dataset.weights.split(',').map(Number);
weights = { i: wi, c: wc, s: ws, k: wk };
document.getElementById('sl-w-i').value = wi;
document.getElementById('sl-w-c').value = wc;
document.getElementById('sl-w-s').value = ws;
document.getElementById('sl-w-k').value = wk;
document.getElementById('lbl-w-i').textContent = wi + '%';
document.getElementById('lbl-w-c').textContent = wc + '%';
document.getElementById('lbl-w-s').textContent = ws + '%';
document.getElementById('lbl-w-k').textContent = wk + '%';
refreshAll();
});
['i', 'c', 's', 'k'].forEach(axis => {
document.getElementById(`sl-w-${axis}`).addEventListener('input', (e) => {
weights[axis] = Number(e.target.value);
document.getElementById(`lbl-w-${axis}`).textContent = weights[axis] + '%';
refreshAll();
});
});
document.getElementById('search-input').addEventListener('input', refreshAll);
document.querySelectorAll('#lb-table thead th[data-sort]').forEach(th => {
th.addEventListener('click', () => {
const key = th.dataset.sort;
if (currentSortKey === key) {
currentSortAsc = !currentSortAsc;
} else {
currentSortKey = key;
currentSortAsc = (key === 'name' || key === 'usd' || key === 'p50' || key === 'ece');
}
refreshAll();
});
});
refreshAll();
}
init();
</script>
</body>
</html>
|