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Update src/App.js
Browse files- src/App.js +154 -157
src/App.js
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import React, { useState, useEffect } from 'react';
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const BenchmarkChart = () => {
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// Real data from your
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const benchmarkData = [
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{
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model: "
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},
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{
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model: "
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{
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model: "
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},
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{
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model: "
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{
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model: "
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},
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{
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model: "GPT o3",
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},
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{
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model: "
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root_problem: 26
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},
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{
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model: "
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},
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{
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model: "
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}
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];
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const [currentPhase, setCurrentPhase] = useState('baseline');
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const [currentMethodIndex, setCurrentMethodIndex] = useState(0);
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const synthesisMethodsOrder = ['keyword_objective_combined', '
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const phases = [
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{ key: 'baseline', label: '
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{ key: 'additive_synthesis', label: '
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];
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useEffect(() => {
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const interval = setInterval(() => {
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setCurrentPhase(prev => prev === 'baseline' ? 'additive_synthesis' : 'baseline');
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setCurrentMethodIndex(0);
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},
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return () => clearInterval(interval);
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}, []);
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@@ -83,199 +116,163 @@ const BenchmarkChart = () => {
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const methodInterval = setInterval(() => {
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setCurrentMethodIndex(prev => {
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const nextIndex = prev + 1;
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// Stay at final state (all methods added) for longer
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if (nextIndex > synthesisMethodsOrder.length) {
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return synthesisMethodsOrder.length;
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}
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return nextIndex;
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});
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},
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return () => clearInterval(methodInterval);
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}
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}, [currentPhase]);
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const getCurrentValue = (modelData, phase) => {
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if (phase === 'baseline') {
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return modelData.
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} else if (phase === 'additive_synthesis') {
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// Add each synthesis method's contribution up to currentMethodIndex
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for (let i = 0; i < currentMethodIndex; i++) {
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const method = synthesisMethodsOrder[i];
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if (modelData[method] !== undefined) {
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}
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}
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return
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}
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return 0;
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};
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const
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if (phase === 'baseline') return
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const
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for (let i = 0; i < currentMethodIndex; i++) {
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const method = synthesisMethodsOrder[i];
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if (modelData[method] !== undefined) {
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}
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}
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};
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const getBarColor = (modelData, phase) => {
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if (phase === 'baseline') {
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return 'from-blue-500 to-blue-600';
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} else if (phase === 'additive_synthesis' && currentMethodIndex > 0) {
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// Only turn green when we've actually started adding methods
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return 'from-green-500 to-green-600';
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} else {
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// Stay blue if we're in additive phase but haven't started adding yet
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return 'from-blue-500 to-blue-600';
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}
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};
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return (
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<div className="min-h-screen bg-gradient-to-br from-slate-900 to-slate-800 p-
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<div className="max-w-6xl mx-auto">
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{/* Header */}
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<div className="text-center mb-
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<h1 className="text-
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LLM
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</h1>
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<p className="text-slate-300
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SafetyBench Aug 2025 -
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</p>
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{/* Methodology
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<div className="mt-
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<div className="flex items-start space-x-3">
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<div className="text-left">
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<p className="text-yellow-200 font-semibold mb-2">Methodology Note</p>
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<p className="text-yellow-100 text-sm leading-relaxed">
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<strong>Additive Visualization:</strong> This chart shows cumulative impact by progressively adding each synthesis method's individual attack success rate.
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Values >100% represent
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Results are based on HarmBench Grading methodology and should be interpreted as relative performance indicators.
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</p>
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</div>
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</div>
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</div>
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<div className="mt-4 p-4 bg-slate-800 rounded-lg inline-block">
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<p className="text-white font-semibold">
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Current View: {phases.find(p => p.key === currentPhase)?.label}
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</p>
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{currentPhase === 'additive_synthesis' && currentMethodIndex > 0 && (
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<p className="text-slate-300 text-sm mt-1">
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Adding Method {currentMethodIndex}: {synthesisMethodsOrder[currentMethodIndex - 1]?.replace(/_/g, ' ').replace(/\b\w/g, l => l.toUpperCase())}
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</p>
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)}
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</div>
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</div>
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{/* Chart Container */}
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<div className="bg-white rounded-
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<div className="
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{
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<div className="flex-1">
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<
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<
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</div>
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)}
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{currentPhase === 'additive_synthesis' && (
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<div className="text-xs text-gray-500 flex flex-wrap gap-x-4 gap-y-1">
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<span className="text-blue-600">Base: {baselineValue.toFixed(1)}%</span>
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{currentMethodIndex === 0 && (
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<span className="text-gray-400">Starting to add methods...</span>
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)}
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{synthesisMethodsOrder.slice(0, currentMethodIndex).map(method => {
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if (modelData[method] !== undefined) {
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return (
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<span key={method} className="text-green-600">
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+{method.replace(/_/g, ' ')}: {modelData[method].toFixed(1)}%
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</span>
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);
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}
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return null;
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})}
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</div>
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)}
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</div>
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</div>
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</div>
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)}
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</div>
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</div>
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{/* Progress Bar */}
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<div className="relative h-12 bg-gray-200 rounded-full overflow-hidden">
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<div
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className={`h-full bg-gradient-to-r ${getBarColor(modelData, currentPhase)} rounded-full transition-all duration-[2000ms] ease-out flex items-center justify-end pr-4`}
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style={{ width: `${Math.max(barWidth, 5)}%` }}
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>
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<div className="text-white font-semibold text-sm">
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{currentValue > 8 ? `${currentValue.toFixed(1)}%` : ''}
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</div>
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</div>
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</div>
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)
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</div>
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{/* Legend */}
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<div className="mt-
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<div className="flex items-center space-x-2">
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<div className="w-
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<span className="text-gray-700">Baseline
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</div>
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<div className="flex items-center space-x-2">
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<div className="w-
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<span className="text-gray-700">
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</div>
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</div>
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</div>
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{/* Footer
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<div className="mt-
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<p className="text-sm">
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</p>
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<div className="text-xs mt-4 max-w-4xl mx-auto space-y-1">
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</div>
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</div>
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</div>
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</div>
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import React, { useState, useEffect } from 'react';
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const BenchmarkChart = () => {
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// Real data from your ASR calculations - sorted by highest achievable ASR
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const benchmarkData = [
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{
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model: "Grok 4",
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baseline: 68.67,
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methods: {
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keyword_objective_combined: 85.15
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}
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},
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{
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model: "Deepseek R1-0528",
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baseline: 68.67,
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methods: {
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keyword_objective_combined: 83.76
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}
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},
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{
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model: "Llama 3.1 405B",
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baseline: 67.00,
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methods: {
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keyword_objective_combined: 80.75
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}
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},
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{
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model: "Gemini 2.5 Pro",
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baseline: 55.67,
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methods: {
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keyword_objective_combined: 74.14,
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root_problem: 67.19
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}
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},
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{
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model: "Llama 3 8B Instruct Reference",
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baseline: 58.33,
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methods: {
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keyword_objective_combined: 68.86
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}
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},
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{
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model: "Mixtral 8x22B",
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baseline: 48.00,
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methods: {
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keyword_objective_combined: 66.82
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}
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},
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{
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model: "Llama 4 Maverick Instruct",
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baseline: 45.00,
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methods: {
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keyword_objective_combined: 56.46
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}
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},
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{
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model: "GPT o3",
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baseline: 22.00,
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methods: {
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keyword_objective_combined: 30.53
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}
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},
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{
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model: "Claude 4 Sonnet",
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baseline: 26.33,
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methods: {
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keyword_objective_combined: 28.64
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}
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},
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{
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model: "Claude Opus 4.1",
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baseline: 20.67,
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methods: {
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keyword_objective_combined: 23.56
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}
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},
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{
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model: "GPT 5",
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baseline: 8.33,
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methods: {
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keyword_objective_combined: 11.68,
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root_problem: 12.46
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}
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},
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{
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model: "GPT 5 mini",
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baseline: 7.67,
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methods: {
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keyword_objective_combined: 11.28,
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root_problem: 10.44
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}
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}
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];
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const [currentPhase, setCurrentPhase] = useState('baseline');
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const [currentMethodIndex, setCurrentMethodIndex] = useState(0);
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const synthesisMethodsOrder = ['keyword_objective_combined', 'root_problem'];
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const phases = [
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{ key: 'baseline', label: 'Human Baseline ASR' },
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{ key: 'additive_synthesis', label: 'Human + Synthesis Methods ASR' }
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];
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useEffect(() => {
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const interval = setInterval(() => {
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setCurrentPhase(prev => prev === 'baseline' ? 'additive_synthesis' : 'baseline');
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setCurrentMethodIndex(0);
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}, 8000);
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return () => clearInterval(interval);
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}, []);
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const methodInterval = setInterval(() => {
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setCurrentMethodIndex(prev => {
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const nextIndex = prev + 1;
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if (nextIndex > synthesisMethodsOrder.length) {
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return synthesisMethodsOrder.length;
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}
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return nextIndex;
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});
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}, 2000);
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return () => clearInterval(methodInterval);
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}
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}, [currentPhase]);
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const getCurrentValue = (modelData, phase) => {
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if (phase === 'baseline') {
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return modelData.baseline;
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} else if (phase === 'additive_synthesis') {
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// Show the highest ASR achieved by any method tried so far
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let maxASR = modelData.baseline;
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for (let i = 0; i < currentMethodIndex; i++) {
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const method = synthesisMethodsOrder[i];
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if (modelData.methods[method] !== undefined) {
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maxASR = Math.max(maxASR, modelData.methods[method]);
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}
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}
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return maxASR;
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}
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return 0;
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};
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const getCurrentMethod = (modelData, phase) => {
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if (phase === 'baseline') return 'Human Baseline';
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if (currentMethodIndex === 0) return 'Human Baseline';
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const availableMethods = [];
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for (let i = 0; i < currentMethodIndex; i++) {
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const method = synthesisMethodsOrder[i];
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if (modelData.methods[method] !== undefined) {
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availableMethods.push(method);
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}
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}
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if (availableMethods.length === 0) return 'Human Baseline';
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return availableMethods[availableMethods.length - 1].replace(/_/g, ' ').replace(/\b\w/g, l => l.toUpperCase());
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};
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const getBarColor = (modelData, phase) => {
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if (phase === 'baseline') {
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return 'from-blue-500 to-blue-600';
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} else if (phase === 'additive_synthesis' && currentMethodIndex > 0) {
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return 'from-green-500 to-green-600';
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} else {
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return 'from-blue-500 to-blue-600';
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}
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};
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return (
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<div className="min-h-screen bg-gradient-to-br from-slate-900 to-slate-800 p-4">
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<div className="max-w-6xl mx-auto">
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{/* Header */}
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<div className="text-center mb-6">
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<h1 className="text-3xl font-bold text-white mb-3">
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LLM Attack Success Rate with Synthesis Methods
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</h1>
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<p className="text-slate-300">
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SafetyBench Aug 2025 - Real ASR Calculations
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</p>
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{/* Methodology Note */}
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<div className="mt-4 p-3 bg-yellow-900/30 border border-yellow-500/30 rounded-lg max-w-4xl mx-auto">
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<div className="flex items-start space-x-3">
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<div className="text-yellow-400 mt-1">⚠️</div>
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<div className="text-left">
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<p className="text-yellow-200 font-semibold mb-2">Methodology Note</p>
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<p className="text-yellow-100 text-sm leading-relaxed">
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<strong>Additive Visualization:</strong> This chart shows cumulative impact by progressively adding each synthesis method's individual attack success rate.
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Values >100% represent synthesis of multiple conversations off one failed, human seed conversation.
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Results are based on HarmBench Grading methodology and should be interpreted as relative performance indicators.
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</p>
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</div>
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</div>
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</div>
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</div>
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{/* Chart Container - Scrollable Box */}
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<div className="bg-white rounded-xl shadow-2xl p-4">
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<div className="h-96 overflow-y-auto pr-2">
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<div className="space-y-2">
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{benchmarkData.map((modelData, index) => {
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const currentValue = getCurrentValue(modelData, currentPhase);
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const baselineValue = modelData.baseline;
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const maxValue = 90;
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const barWidth = (currentValue / maxValue) * 100;
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const currentMethod = getCurrentMethod(modelData, currentPhase);
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const gain = currentValue - baselineValue;
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return (
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<div key={modelData.model} className="relative">
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{/* Model Name and Value */}
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<div className="flex items-center justify-between mb-1">
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<div>
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<h3 className="font-semibold text-gray-800 text-sm">
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{modelData.model}
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</h3>
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<p className="text-xs text-gray-600">
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{currentMethod}
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</p>
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</div>
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<div className="text-right">
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<span className="text-lg font-bold text-gray-700">
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{currentValue.toFixed(1)}%
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</span>
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{gain > 0 && (
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<div className="text-xs font-semibold text-green-600">
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+{gain.toFixed(1)} points
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</div>
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)}
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</div>
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</div>
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{/* Progress Bar */}
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<div className="relative h-6 bg-gray-200 rounded-full overflow-hidden">
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<div
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className={`h-full bg-gradient-to-r ${getBarColor(modelData, currentPhase)} rounded-full transition-all duration-2000 ease-out flex items-center justify-end pr-2`}
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style={{ width: `${Math.max(barWidth, 5)}%` }}
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>
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<div className="text-white font-semibold text-xs">
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{currentValue > 8 ? `${currentValue.toFixed(1)}%` : ''}
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</div>
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</div>
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</div>
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</div>
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);
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})}
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</div>
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</div>
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{/* Legend */}
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<div className="mt-4 pt-4 border-t border-gray-200 flex justify-center space-x-6 text-sm">
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<div className="flex items-center space-x-2">
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<div className="w-3 h-3 bg-gradient-to-r from-blue-500 to-blue-600 rounded"></div>
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<span className="text-gray-700">Human Baseline</span>
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</div>
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<div className="flex items-center space-x-2">
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<div className="w-3 h-3 bg-gradient-to-r from-green-500 to-green-600 rounded"></div>
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<span className="text-gray-700">With Synthesis Methods</span>
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</div>
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</div>
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</div>
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{/* Footer */}
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<div className="mt-4 text-center text-slate-400 space-y-1">
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<p className="text-sm">
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Top performers: Grok 4 (85.15%), Deepseek R1-0528 (83.76%), Llama 3.1 405B (80.75%)
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</p>
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<p className="text-xs">
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Shows highest ASR achieved when combining human attempts with synthesis methods
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</p>
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</div>
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</div>
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</div>
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