ELPO: Ensemble Learning Based Prompt Optimization

QianXun (QianXun) • 2025年11月24日 16:25
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    <title>ELPO：基于集成学习的提示词优化深度研究</title>
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            <a href="#executive-summary" class="block py-1 text-gray-600 hover:text-blue-600 transition-colors">内容摘要</a>
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            <div class="space-y-6">
              <h1 class="text-5xl font-bold serif italic leading-tight">
                ELPO: <em class="text-yellow-200">Ensemble Learning</em>
                <br/>
                Based Prompt Optimization
              </h1>
              <p class="text-xl text-blue-100 leading-relaxed">
                一项通过集成学习革新自动提示词优化的深度解析框架，显著提升了准确性、鲁棒性及泛化能力。
              </p>
              <div class="flex flex-wrap gap-4">
                <span class="px-4 py-2 bg-white bg-opacity-20 rounded-full text-sm font-medium">集成学习</span>
                <span class="px-4 py-2 bg-white bg-opacity-20 rounded-full text-sm font-medium">提示词优化</span>
                <span class="px-4 py-2 bg-white bg-opacity-20 rounded-full text-sm font-medium">黑盒优化</span>
              </div>
            </div>
            <div class="glass-effect rounded-2xl p-8">
              <img src="https://kimi-web-img.moonshot.cn/img/i-blog.csdnimg.cn/ba3e40cd77e3e7bacb9792507b137bad6afd6a7f.png" alt="集成学习概念的可视化展示" class="w-full h-48 object-cover rounded-lg mb-4" size="medium" aspect="wide" query="集成学习概念图" referrerpolicy="no-referrer" data-modified="1" data-score="0.00"/>
              <p class="text-sm text-gray-600 italic">
                ELPO 框架整合了多种生成策略与搜索算法，借助稳健的集成投票机制选择最终提示词。
              </p>
            </div>
          </div>
        </div>
      </section>

      <!-- 内容摘要 -->
      <section id="executive-summary" class="py-16 bg-white">
        <div class="container mx-auto px-8">
          <h2 class="text-3xl font-bold serif mb-8 text-center">内容摘要</h2>
          <div class="grid md:grid-cols-3 gap-8">
            <div class="performance-card p-6 rounded-xl">
              <div class="flex items-center mb-4">
                <i class="fas fa-chart-line text-2xl text-blue-600 mr-3"></i>
                <h3 class="text-xl font-semibold">性能提升</h3>
              </div>
              <p class="text-gray-700">
                ELPO 在 ArSarcasm 数据集上 F1 分数提升 7.6 分，优于当前最先进方法，并在多个基准测试中保持持续领先。
              </p>
            </div>
            <div class="innovation-card p-6 rounded-xl">
              <div class="flex items-center mb-4">
                <i class="fas fa-lightbulb text-2xl text-yellow-600 mr-3"></i>
                <h3 class="text-xl font-semibold">核心创新</h3>
              </div>
              <p class="text-gray-700">
                集成Hard-Case Tracking、贝叶斯优化、多臂老虎机(MAB)及集成投票机制，打造稳健的提示词优化解决方案。
              </p>
            </div>
            <div class="application-card p-6 rounded-xl">
              <div class="flex items-center mb-4">
                <i class="fas fa-cogs text-2xl text-green-600 mr-3"></i>
                <h3 class="text-xl font-semibold">实际应用</h3>
              </div>
              <p class="text-gray-700">
                专为黑盒 LLM 优化设计，通过 API 交互，在确保性能的同时大幅降低 LLM API 调用次数。
              </p>
            </div>
          </div>
        </div>
      </section>

      <!-- 核心方法论 -->
      <section id="core-methodology" class="py-16 bg-gray-50">
        <div class="container mx-auto px-8">
          <h2 class="text-3xl font-bold serif mb-12 text-center">核心方法论</h2>

          <div class="mb-16">
            <h3 class="text-2xl font-semibold mb-6">总体框架：集成学习驱动优化</h3>
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <p class="text-gray-700 mb-6">
                ELPO 通过三大核心要素直面传统 APO 的局限性：
                <strong>共享生成策略</strong>、<strong>多样化搜索方法</strong>及<strong>集成投票机制</strong>。
                <a href="https://arxiv.org/html/2511.16122" class="citation-link" target="_blank">[1]</a>
              </p>
              <div class="grid md:grid-cols-3 gap-6">
                <div class="text-center p-4 bg-blue-50 rounded-lg">
                  <i class="fas fa-cube text-3xl text-blue-600 mb-3"></i>
                  <h4 class="font-semibold mb-2">生成策略</h4>
                  <p class="text-sm text-gray-600">多生成器框架，提升候选词多样性与质量</p>
                </div>
                <div class="text-center p-4 bg-green-50 rounded-lg">
                  <i class="fas fa-search text-3xl text-green-600 mb-3"></i>
                  <h4 class="font-semibold mb-2">搜索算法</h4>
                  <p class="text-sm text-gray-600">贝叶斯优化与 MAB 提升搜索效率</p>
                </div>
                <div class="text-center p-4 bg-purple-50 rounded-lg">
                  <i class="fas fa-vote-yea text-3xl text-purple-600 mb-3"></i>
                  <h4 class="font-semibold mb-2">集成投票</h4>
                  <p class="text-sm text-gray-600">稳健投票机制选择最终提示词</p>
                </div>
              </div>
            </div>
          </div>

          <div class="mb-16">
            <h3 class="text-2xl font-semibold mb-6">Hard-Case Tracking 策略</h3>
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <div class="flex items-start space-x-6">
                <img src="https://kimi-web-img.moonshot.cn/img/pocdn.processon.com/a194a75d0a935d0f67bc489cd0d7379cfac4eff3.png" alt="错误分析流程示意图" class="w-1/3 h-48 object-cover rounded-lg" size="medium" aspect="wide" query="错误分析流程" referrerpolicy="no-referrer" data-modified="1" data-score="0.00"/>
                <div class="flex-1">
                  <p class="text-gray-700 mb-4">
                    Hard-Case Tracking 是 ELPO 的创新核心策略，专注于分析持续出错的样本及导致错误的提示，利用 LLM 生成更具鲁棒性的提示。
                    <a href="https://arxiv.org/html/2511.16122" class="citation-link" target="_blank">[1]</a>
                  </p>
                  <ul class="space-y-2 text-gray-700">
                    <li class="flex items-start">
                      <i class="fas fa-check-circle text-green-500 mr-2 mt-1"></i>
                      <span>识别多次迭代中持续误分类的样本</span>
                    </li>
                    <li class="flex items-start">
                      <i class="fas fa-check-circle text-green-500 mr-2 mt-1"></i>
                      <span>分析错误提示，理解根本原因</span>
                    </li>
                    <li class="flex items-start">
                      <i class="fas fa-check-circle text-green-500 mr-2 mt-1"></i>
                      <span>生成更具泛化能力的改进提示</span>
                    </li>
                  </ul>
                </div>
              </div>
            </div>
          </div>

          <div class="mb-16">
            <h3 class="text-2xl font-semibold mb-6">高效搜索算法</h3>
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <div class="grid md:grid-cols-2 gap-8">
                <div>
                  <h4 class="text-xl font-semibold mb-4 text-blue-600">贝叶斯优化</h4>
                  <p class="text-gray-700 mb-4">
                    通过高斯过程回归及期望改进采集函数，将提示映射至连续高维空间，实现高效优化。
                    <a href="https://arxiv.org/pdf/2511.16122" class="citation-link" target="_blank">[2]</a>
                  </p>
                  <div class="bg-blue-50 p-4 rounded-lg">
                    <h5 class="font-semibold mb-2">主要优点：</h5>
                    <ul class="text-sm space-y-1">
                      <li>• 减少 LLM API 调用</li>
                      <li>• 智能探索-利用权衡</li>
                      <li>• 连续空间优化</li>
                    </ul>
                  </div>
                </div>
                <div>
                  <h4 class="text-xl font-semibold mb-4 text-green-600">多臂老虎机</h4>
                  <p class="text-gray-700 mb-4">
                    候选提示聚类后以各簇为臂，上置信界(UCB)准则引导探索，高效分配评估资源。
                    <a href="https://arxiv.org/html/2511.16122" class="citation-link" target="_blank">[1]</a>
                  </p>
                  <div class="bg-green-50 p-4 rounded-lg">
                    <h5 class="font-semibold mb-2">主要优点：</h5>
                    <ul class="text-sm space-y-1">
                      <li>• 首次应用于APO领域</li>
                      <li>• 结构化提示选择</li>
                      <li>• 高效资源分配</li>
                    </ul>
                  </div>
                </div>
              </div>
            </div>
          </div>
        </div>
      </section>

      <!-- 性能对比 -->
      <section id="performance-comparison" class="py-16 bg-white">
        <div class="container mx-auto px-8">
          <h2 class="text-3xl font-bold serif mb-12 text-center">性能对比与实验评估</h2>

          <div class="mb-16">
            <h3 class="text-2xl font-semibold mb-6">性能优势</h3>
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <p class="text-gray-700 mb-6">
                ELPO 始终优于现有最先进方法，在分类、生成及多选等多样任务中均表现出色。
                <a href="https://arxiv.org/pdf/2511.16122" class="citation-link" target="_blank">[2]</a>
              </p>

              <div class="grid md:grid-cols-2 gap-8">
                <div class="bg-gradient-to-r from-blue-50 to-blue-100 p-6 rounded-lg">
                  <h4 class="text-lg font-semibold text-blue-800 mb-3">ArSarcasm 数据集（F1分数）</h4>
                  <div class="text-center">
                    <div class="text-3xl font-bold text-blue-600 mb-2">+7.6</div>
                    <p class="text-blue-700">F1 分数提升（对比SOTA方法）</p>
                  </div>
                </div>
                <div class="bg-gradient-to-r from-green-50 to-green-100 p-6 rounded-lg">
                  <h4 class="text-lg font-semibold text-green-800 mb-3">任务覆盖范围</h4>
                  <ul class="text-green-700 space-y-1">
                    <li>• 文本分类</li>
                    <li>• 生成式问答</li>
                    <li>• 多选推理</li>
                    <li>• 数学问题求解</li>
                  </ul>
                </div>
              </div>
            </div>
          </div>

          <div class="mb-16">
            <h3 class="text-2xl font-semibold mb-6">实验数据集</h3>
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <div class="overflow-x-auto">
                <table class="w-full text-sm">
                  <thead>
                    <tr class="border-b">
                      <th class="text-left py-3 px-4 font-semibold">数据集</th>
                      <th class="text-left py-3 px-4 font-semibold">任务类型</th>
                      <th class="text-left py-3 px-4 font-semibold">主要挑战</th>
                    </tr>
                  </thead>
                  <tbody class="divide-y">
                    <tr>
                      <td class="py-3 px-4 font-medium">ArSarcasm</td>
                      <td class="py-3 px-4">文本分类</td>
                      <td class="py-3 px-4">阿拉伯语讽刺检测</td>
                    </tr>
                    <tr>
                      <td class="py-3 px-4 font-medium">LIAR</td>
                      <td class="py-3 px-4">文本分类</td>
                      <td class="py-3 px-4">谎言检测</td>
                    </tr>
                    <tr>
                      <td class="py-3 px-4 font-medium">BBH-navigate</td>
                      <td class="py-3 px-4">多选</td>
                      <td class="py-3 px-4">导航推理</td>
                    </tr>
                    <tr>
                      <td class="py-3 px-4 font-medium">GSM8K</td>
                      <td class="py-3 px-4">生成式问答</td>
                      <td class="py-3 px-4">数学问题解决</td>
                    </tr>
                  </tbody>
                </table>
              </div>
              <p class="text-gray-600 text-sm mt-4">
                <a href="https://www.themoonlight.io/zh/review/elpo-ensemble-learning-based-prompt-optimization-for-large-language-models" class="citation-link" target="_blank">[17]</a>
              </p>
            </div>
          </div>

          <div class="mb-16">
            <h3 class="text-2xl font-semibold mb-6">消融研究</h3>
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <p class="text-gray-700 mb-6">
                全面的消融研究验证了 ELPO 各独立组件的有效性及其对整体性能的贡献。
                <a href="https://arxiv.org/pdf/2511.16122" class="citation-link" target="_blank">[2]</a>
              </p>

              <div class="grid md:grid-cols-3 gap-6">
                <div class="text-center p-4 bg-red-50 rounded-lg border border-red-200">
                  <h4 class="font-semibold text-red-800 mb-2">无 Hard-Case Tracking</h4>
                  <p class="text-red-600 text-sm">性能大幅下降，证实其在泛化能力提升中的关键作用</p>
                </div>
                <div class="text-center p-4 bg-yellow-50 rounded-lg border border-yellow-200">
                  <h4 class="font-semibold text-yellow-800 mb-2">基础搜索方法</h4>
                  <p class="text-yellow-600 text-sm">效率降低，突显贝叶斯+MAB优化的必要性</p>
                </div>
                <div class="text-center p-4 bg-blue-50 rounded-lg border border-blue-200">
                  <h4 class="font-semibold text-blue-800 mb-2">单一提示选择</h4>
                  <p class="text-blue-600 text-sm">性能波动增大，证明集成投票机制的价值</p>
                </div>
              </div>
            </div>
          </div>
        </div>
      </section>

      <!-- 应用场景 -->
      <section id="applications" class="py-16 bg-gray-50">
        <div class="container mx-auto px-8">
          <h2 class="text-3xl font-bold serif mb-12 text-center">潜在应用场景与价值</h2>

          <div class="grid md:grid-cols-2 gap-8 mb-16">
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <h3 class="text-xl font-semibold mb-4 text-blue-600">自然语言处理任务</h3>
              <div class="space-y-4">
                <div class="flex items-start space-x-3">
                  <i class="fas fa-comments text-green-500 mt-1"></i>
                  <div>
                    <h4 class="font-medium">文本分类与情感分析</h4>
                    <p class="text-sm text-gray-600">通过讽刺检测（ArSarcasm）和仇恨言论检测（ETHOS）等复杂情感识别提升分类精度</p>
                  </div>
                </div>
                <div class="flex items-start space-x-3">
                  <i class="fas fa-question-circle text-blue-500 mt-1"></i>
                  <div>
                    <h4 class="font-medium">问答与阅读理解</h4>
                    <p class="text-sm text-gray-600">优化多步推理与代词消解（WSC）的提示词，改善逻辑理解能力</p>
                  </div>
                </div>
                <div class="flex items-start space-x-3">
                  <i class="fas fa-calculator text-purple-500 mt-1"></i>
                  <div>
                    <h4 class="font-medium">复杂推理与数学</h4>
                    <p class="text-sm text-gray-600">增强数学问题求解（GSM8K）与多步逻辑推理能力</p>
                  </div>
                </div>
              </div>
            </div>

            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <h3 class="text-xl font-semibold mb-4 text-green-600">挑战应对</h3>
              <div class="space-y-4">
                <div class="flex items-start space-x-3">
                  <i class="fas fa-lock text-red-500 mt-1"></i>
                  <div>
                    <h4 class="font-medium">黑盒优化</h4>
                    <p class="text-sm text-gray-600">适用于闭源 LLM API，无需模型内部信息访问权限</p>
                  </div>
                </div>
                <div class="flex items-start space-x-3">
                  <i class="fas fa-tachometer-alt text-orange-500 mt-1"></i>
                  <div>
                    <h4 class="font-medium">效率提升</h4>
                    <p class="text-sm text-gray-600">智能搜索算法显著减少LLM API调用，降低计算浪费</p>
                  </div>
                </div>
                <div class="flex items-start space-x-3">
                  <i class="fas fa-shield-alt text-blue-500 mt-1"></i>
                  <div>
                    <h4 class="font-medium">泛化能力增强</h4>
                    <p class="text-sm text-gray-600">生成具备跨领域及任务稳健泛化的提示词</p>
                  </div>
                </div>
              </div>
            </div>
          </div>

          <div class="bg-white p-8 rounded-xl shadow-sm border">
            <h3 class="text-2xl font-semibold mb-6 text-center">实际应用价值</h3>
            <div class="grid md:grid-cols-3 gap-6">
              <div class="text-center p-6 bg-gradient-to-b from-blue-50 to-blue-100 rounded-lg">
                <i class="fas fa-industry text-3xl text-blue-600 mb-4"></i>
                <h4 class="font-semibold mb-2">企业 AI</h4>
                <p class="text-sm text-gray-600">为各类商业场景提供高质量的提示词优化，提升 LLM 应用效果</p>
              </div>
              <div class="text-center p-6 bg-gradient-to-b from-green-50 to-green-100 rounded-lg">
                <i class="fas fa-graduation-cap text-3xl text-green-600 mb-4"></i>
                <h4 class="font-semibold mb-2">学术研究</h4>
                <p class="text-sm text-gray-600">为研究人员提供高效的提示词工程系统，助力各类语言任务研究</p>
              </div>
              <div class="text-center p-6 bg-gradient-to-b from-purple-50 to-purple-100 rounded-lg">
                <i class="fas fa-rocket text-3xl text-purple-600 mb-4"></i>
                <h4 class="font-semibold mb-2">产品开发</h4>
                <p class="text-sm text-gray-600">加速 AI 产品迭代，实现高效的提示词优化与测试流程</p>
              </div>
            </div>
          </div>
        </div>
      </section>

      <!-- 相关研究 -->
      <section id="related-research" class="py-16 bg-white">
        <div class="container mx-auto px-8">
          <h2 class="text-3xl font-bold serif mb-12 text-center">相关研究与技术背景</h2>

          <div class="mb-16">
            <h3 class="text-2xl font-semibold mb-6">APO 演进历程</h3>
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <div class="space-y-8">
                <div class="flex items-start space-x-4">
                  <div class="flex-shrink-0 w-12 h-12 bg-blue-100 rounded-full flex items-center justify-center">
                    <span class="text-blue-600 font-bold">1</span>
                  </div>
                  <div>
                    <h4 class="text-lg font-semibold mb-2">早期方法（搜索与进化）</h4>
                    <p class="text-gray-700 mb-2">
                      APE 采用蒙特卡洛搜索，PromptAgent 利用树搜索结构，EvoPrompt 应用进化算法。
                      <a href="https://arxiv.org/pdf/2511.16122" class="citation-link" target="_blank">[2]</a>
                    </p>
                    <div class="bg-red-50 p-3 rounded border-l-4 border-red-400">
                      <p class="text-red-700 text-sm"><strong>局限：</strong>效率低、资源消耗大、缺乏方向性</p>
                    </div>
                  </div>
                </div>

                <div class="flex items-start space-x-4">
                  <div class="flex-shrink-0 w-12 h-12 bg-green-100 rounded-full flex items-center justify-center">
                    <span class="text-green-600 font-bold">2</span>
                  </div>
                  <div>
                    <h4 class="text-lg font-semibold mb-2">反馈驱动方法</h4>
                    <p class="text-gray-700 mb-2">
                      ProTeGi 引入“文本梯度”，利用 LLM 反馈指导提示词优化，提升方向性。
                      <a href="https://arxiv.org/pdf/2511.16122" class="citation-link" target="_blank">[2]</a>
                    </p>
                    <div class="bg-yellow-50 p-3 rounded border-l-4 border-yellow-400">
                      <p class="text-yellow-700 text-sm"><strong>局限：</strong>依赖单一算法，历史信息未充分利用</p>
                    </div>
                  </div>
                </div>

                <div class="flex items-start space-x-4">
                  <div class="flex-shrink-0 w-12 h-12 bg-purple-100 rounded-full flex items-center justify-center">
                    <span class="text-purple-600 font-bold">3</span>
                  </div>
                  <div>
                    <h4 class="text-lg font-semibold mb-2">ELPO 创新</h4>
                    <p class="text-gray-700 mb-2">
                      首次将集成学习思想引入 APO，系统性解决性能不稳定性与不鲁棒问题。
                      <a href="https://arxiv.org/pdf/2511.16122" class="citation-link" target="_blank">[2]</a>
                    </p>
                    <div class="bg-green-50 p-3 rounded border-l-4 border-green-400">
                      <p class="text-green-700 text-sm"><strong>突破：</strong>多策略聚合、高效搜索、稳健决策</p>
                    </div>
                  </div>
                </div>
              </div>
            </div>
          </div>

          <div class="mb-16">
            <h3 class="text-2xl font-semibold mb-6">现有方法局限</h3>
            <div class="bg-white p-8 rounded-xl shadow-sm border">
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                  <h4 class="font-semibold text-red-800 mb-2">单一算法依赖</h4>
                  <p class="text-red-700 text-sm">性能易波动，缺乏跨任务通用性</p>
                </div>
                <div class="text-center p-6 bg-yellow-50 rounded-lg border border-yellow-200">
                  <i class="fas fa-history text-3xl text-yellow-600 mb-4"></i>
                  <h4 class="font-semibold text-yellow-800 mb-2">历史信息利用不足</h4>
                  <p class="text-yellow-700 text-sm">迭代反馈未保存，重复探索导致效率低下</p>
                </div>
                <div class="text-center p-6 bg-orange-50 rounded-lg border border-orange-200">
                  <i class="fas fa-compass text-3xl text-orange-600 mb-4"></i>
                  <h4 class="font-semibold text-orange-800 mb-2">搜索方向性不足</h4>
                  <p class="text-orange-700 text-sm">对提示空间的探索不系统，缺乏明确方向</p>
                </div>
              </div>
            </div>
          </div>

          <div class="bg-white p-8 rounded-xl shadow-sm border">
            <h3 class="text-2xl font-semibold mb-6 text-center">ELPO 创新定位</h3>
            <div class="text-center mb-8">
              <img src="https://kimi-web-img.moonshot.cn/img/i-blog.csdnimg.cn/ba3e40cd77e3e7bacb9792507b137bad6afd6a7f.png" alt="集成学习框架示意图" class="w-full max-w-2xl mx-auto h-64 object-cover rounded-lg" size="medium" aspect="wide" query="集成学习框架" referrerpolicy="no-referrer" data-modified="1" data-score="0.00"/>
            </div>
            <div class="grid md:grid-cols-2 gap-8">
              <div>
                <h4 class="text-lg font-semibold mb-4 text-blue-600">集成范式</h4>
                <ul class="space-y-2 text-gray-700">
                  <li class="flex items-start">
                    <i class="fas fa-check text-green-500 mr-2 mt-1"></i>
                    <span>多策略生成兼顾深度与广度</span>
                  </li>
                  <li class="flex items-start">
                    <i class="fas fa-check text-green-500 mr-2 mt-1"></i>
                    <span>高效互补的搜索算法</span>
                  </li>
                  <li class="flex items-start">
                    <i class="fas fa-check text-green-500 mr-2 mt-1"></i>
                    <span>稳健投票机制，实现优势互补</span>
                  </li>
                </ul>
              </div>
              <div>
                <h4 class="text-lg font-semibold mb-4 text-purple-600">范式转变</h4>
                <p class="text-gray-700 mb-4">
                  ELPO 将 APO 从寻求“最优单一算法”转变为构建“最优集成系统”，有效解决不稳定性难题。
                  <a href="https://arxiv.org/pdf/2511.16122" class="citation-link" target="_blank">[2]</a>
                </p>
                <div class="bg-purple-50 p-4 rounded-lg">
                  <p class="text-purple-700 text-sm italic">
                    “通过多样性应对不确定性，将 APO 从寻找单一最优解转向构建集成系统。”
                  </p>
                </div>
              </div>
            </div>
          </div>
        </div>
      </section>

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      <section id="technical-deep-dive" class="py-16 bg-gray-50">
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          <h2 class="text-3xl font-bold serif mb-12 text-center">技术深度解析</h2>

          <div class="grid md:grid-cols-2 gap-8 mb-16">
            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <h3 class="text-xl font-semibold mb-4 text-blue-600">贝叶斯优化流程</h3>
              <div class="space-y-4">
                <div class="flex items-center space-x-3">
                  <div class="w-8 h-8 bg-blue-100 rounded-full flex items-center justify-center text-sm font-bold text-blue-600">1</div>
                  <span class="text-sm">高斯过程回归建模提示性能</span>
                </div>
                <div class="flex items-center space-x-3">
                  <div class="w-8 h-8 bg-blue-100 rounded-full flex items-center justify-center text-sm font-bold text-blue-600">2</div>
                  <span class="text-sm">期望改进指导候选选择</span>
                </div>
                <div class="flex items-center space-x-3">
                  <div class="w-8 h-8 bg-blue-100 rounded-full flex items-center justify-center text-sm font-bold text-blue-600">3</div>
                  <span class="text-sm">高维空间实现高效优化</span>
                </div>
              </div>
            </div>

            <div class="bg-white p-8 rounded-xl shadow-sm border">
              <h3 class="text-xl font-semibold mb-4 text-green-600">MAB 集成</h3>
              <div class="space-y-4">
                <div class="flex items-center space-x-3">
                  <div class="w-8 h-8 bg-green-100 rounded-full flex items-center justify-center text-sm font-bold text-green-600">1</div>
                  <span class="text-sm">提示聚类形成多个臂</span>
                </div>
                <div class="flex items-center space-x-3">
                  <div class="w-8 h-8 bg-green-100 rounded-full flex items-center justify-center text-sm font-bold text-green-600">2</div>
                  <span class="text-sm">UCB 准则平衡探索与利用</span>
                </div>
                <div class="flex items-center space-x-3">
                  <div class="w-8 h-8 bg-green-100 rounded-full flex items-center justify-center text-sm font-bold text-green-600">3</div>
                  <span class="text-sm">智能资源分配，提升搜索效率</span>
                </div>
              </div>
            </div>
          </div>

          <div class="bg-white p-8 rounded-xl shadow-sm border">
            <h3 class="text-2xl font-semibold mb-6 text-center">集成投票机制</h3>
            <div class="grid md:grid-cols-3 gap-6">
              <div class="text-center p-6 bg-gradient-to-b from-red-50 to-red-100 rounded-lg">
                <i class="fas fa-users text-3xl text-red-600 mb-4"></i>
                <h4 class="font-semibold text-red-800 mb-2">多样化候选池</h4>
                <p class="text-red-700 text-sm">多个生成策略产出高性能且结构多样的提示</p>
              </div>
              <div class="text-center p-6 bg-gradient-to-b from-yellow-50 to-yellow-100 rounded-lg">
                <i class="fas fa-balance-scale text-3xl text-yellow-600 mb-4"></i>
                <h4 class="font-semibold text-yellow-800 mb-2">民主决策</h4>
                <p class="text-yellow-700 text-sm">投票策略抵消个体偏见，降低性能波动</p>
              </div>
              <div class="text-center p-6 bg-gradient-to-b from-green-50 to-green-100 rounded-lg">
                <i class="fas fa-trophy text-3xl text-green-600 mb-4"></i>
                <h4 class="font-semibold text-green-800 mb-2">稳健输出</h4>
                <p class="text-green-700 text-sm">最终提示在准确性与泛化能力上达到最优平衡</p>
              </div>
            </div>
          </div>
        </div>
      </section>

      <!-- 结论 -->
      <section id="conclusion" class="py-16 bg-white">
        <div class="container mx-auto px-8">
          <h2 class="text-3xl font-bold serif mb-12 text-center">结论</h2>

          <div class="bg-gradient-to-r from-blue-50 to-purple-50 p-8 rounded-xl border">
            <div class="text-center mb-8">
              <img src="https://kimi-web-img.moonshot.cn/img/www.forwardpathway.com/80161ac698d2b9be2c2fbe6364ec41113ebdda60.jpg" alt="人工智能技术突破概念图" class="w-full max-w-3xl mx-auto h-64 object-cover rounded-lg" size="medium" aspect="wide" query="人工智能技术突破" referrerpolicy="no-referrer" data-modified="1" data-score="0.00"/>
            </div>

            <div class="space-y-6">
              <p class="text-lg text-gray-700 leading-relaxed">
                ELPO 代表了自动提示词优化的范式变革，系统性地解决了传统方法在单一算法依赖、搜索效率低下及结果不稳定性等方面的关键局限。
              </p>

              <div class="grid md:grid-cols-3 gap-6">
                <div class="text-center p-4">
                  <i class="fas fa-lightbulb text-3xl text-yellow-600 mb-3"></i>
                  <h3 class="font-semibold mb-2">创新集成</h3>
                  <p class="text-sm text-gray-600">Hard-Case Tracking、贝叶斯优化、MAB 与集成投票的协同融合</p>
                </div>
                <div class="text-center p-4">
                  <i class="fas fa-chart-line text-3xl text-green-600 mb-3"></i>
                  <h3 class="font-semibold mb-2">卓越性能</h3>
                  <p class="text-sm text-gray-600">多数据集、多任务中的持续领先，关键指标显著提升</p>
                </div>
                <div class="text-center p-4">
                  <i class="fas fa-cogs text-3xl text-blue-600 mb-3"></i>
                  <h3 class="font-semibold mb-2">实际适用</h3>
                  <p class="text-sm text-gray-600">高效黑盒优化，显著降低计算需求</p>
                </div>
              </div>

              <div class="bg-white p-6 rounded-lg border">
                <h3 class="text-lg font-semibold mb-4 text-center">研究影响</h3>
                <p class="text-gray-700 text-center">
                  ELPO 首创将集成学习思想引入 APO，为提示词工程领域开辟了全新研究方向。其成功表明，多样性与稳健决策机制的系统性结合，能极大释放 LLM 的应用潜力，推动更具通用性和可靠的 AI 系统发展。
                  <a href="https://arxiv.org/pdf/2511.16122" class="citation-link" target="_blank">[2]</a>
                </p>
              </div>
            </div>
          </div>
        </div>
      </section>

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            <h3 class="text-xl font-semibold mb-4">参考文献</h3>
            <div class="space-y-2 text-sm text-gray-300">
              <p>[1] <a href="https://arxiv.org/html/2511.16122" class="citation-link text-blue-400" target="_blank">ELPO: 基于集成学习的大语言模型提示词优化</a>
              </p>
              <p>[2] <a href="https://arxiv.org/pdf/2511.16122" class="citation-link text-blue-400" target="_blank">ELPO 研究论文 PDF</a>
              </p>
              <p>[17] <a href="https://www.themoonlight.io/zh/review/elpo-ensemble-learning-based-prompt-optimization-for-large-language-models" class="citation-link text-blue-400" target="_blank">ELPO 评测 - Moonlight</a>
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ELPO: Ensemble Learning Based Prompt Optimization

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