Monet: Reasoning in Latent Visual Space visibility AI视觉推理在潜在空间的革命性突破
✨步子哥 (steper) •
2026年01月08日 13:49
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<h1>Monet: Reasoning in Latent Visual Space</h1>
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<i class="material-icons" style="font-size:16px;">visibility</i>
<span>AI视觉推理在潜在空间的革命性突破</span>
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<div class="affiliation">北京大学 | 快手 | MIT 联合团队</div>
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<!-- Introduction & Concept -->
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<div class="card-title">
<i class="material-icons">lightbulb</i>
核心概念：超越像素的"想象之眼"
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<div class="card-content" style="display:flex; gap:20px; align-items:center;">
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<p>Monet旨在让多模态大模型（MLLM）摆脱"看图说话"的笨拙模式，真正拥有类似人类的"想象之眼"。它不再满足于简单的像素识别，而是在高维的<span class="highlight-text">"潜在视觉空间"</span>中进行连续的心理模拟。</p>
<p style="margin-top:10px;"><span class="tag tag-theory">流形假说</span> 数据在高维空间中集中在低维流形上。Monet如同在沙漠中找到了唯一的"绿洲之路"，在低维流形上进行"心理模拟"，避免了维度灾难。</p>
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核心技术架构
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<img src="https://sfile.chatglm.cn/image/e4/e47b8c1f.jpg" alt="Neural Network Structure">
<div class="img-overlay">SFT + RL 框架示意</div>
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<p style="margin-bottom:10px;"><span class="tag tag-sft">SFT (蒸馏微调)</span></p>
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<li><strong>阶段1:</strong> 热身适应图像-文本交错推理</li>
<li><strong>阶段2:</strong> 获取高质量目标潜在嵌入</li>
<li><strong>阶段3:</strong> 无辅助图像下自主生成嵌入</li>
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<p style="margin-top:10px; margin-bottom:5px;"><span class="tag tag-rl">VLPO (策略优化)</span></p>
<p>将连续潜变量纳入强化学习策略梯度，直接根据奖励信号优化"视觉直觉"。</p>
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<div class="card-title">
<i class="material-icons">bar_chart</i>
实验结果与性能
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<p style="margin-bottom:10px;">Monet在常规推理任务和<span class="highlight-text">分布外 (OOD)</span>抽象任务上均显著超越基线模型（如GPT-4V）。</p>
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未来展望与应用
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<div class="app-item">
<img src="https://sfile.chatglm.cn/image/4a/4a1c44e9.jpg" alt="Robot Rescue">
<div class="app-text">机器人救灾：模拟复杂环境，规划安全路径</div>
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<div class="app-item">
<img src="https://sfile.chatglm.cn/image/13/133d6267.jpg" alt="Medical AI">
<div class="app-text">医疗预测：模拟病情演变，辅助诊疗决策</div>
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<p style="margin-top:15px;">当机器拥有"心智模型"，它们将像人类一样在脑海中预演行动后果，开启AI在物理世界应用的新篇章。</p>
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© 2025 Monet Research Team | Visual Reasoning Revolution
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