节目简介
来源：小宇宙
⏱️ Highlights
[00:28] 🔮 Self-Retrospection Distillation: Turning Post-hoc Experiences into Prior Foresight（自我回顾蒸馏：将事后经验转化为事前预见）
[01:38] 🎬 Kandinsky 6.0 Video: Foundation Models for Synchronized Video and Audio Generation（Kandinsky 6.0 Video：用于同步视频与音频生成的基础模型）
[02:49] 🌳 The Trinity:Capability-Driven Recursive Self-Improvement for Multimodal Agents（The Trinity：多模态智能体的能力驱动递归自我改进）
[03:59] 🦾 PDRVLA: A Vision-Language-Action Model with Physical Dynamics Representations（PDRVLA：具有物理动力学表征的视觉—语言—动作模型）
[05:09] 🧭 The Teacher Is a Direction, Not a Destination: Extrapolating RL-Induced Representation Residuals in On-Policy Distillation（教师是方向，而非终点：在同策略蒸馏中外推强化学习诱导的表征残差）
[06:21] 🔍 False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents（虚假前沿：诊断与缓解自我进化搜索智能体中的共同作弊）
[07:32] ⚖️ Jeva: System One Models from First Principles（Jeva：从第一性原理构建系统一模型）
[08:43] 🧠 MemT-1.0: Towards Memory-Native Evolution（MemT-1.0：迈向记忆原生进化）
[09:53] 🤖 Has GPT-6-Astra Achieved Embodied Intelligence?（GPT-6-Astra已经实现具身智能了吗？）
[11:03] 🎨 UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement（UniEvo-VL：用于多模态模型自我改进的同策略自蒸馏训练配方）
[播客论文目录配图]
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小红书: AI速递
[00:28] 🔮 Self-Retrospection Distillation: Turning Post-hoc Experiences into Prior Foresight（自我回顾蒸馏：将事后经验转化为事前预见）
[01:38] 🎬 Kandinsky 6.0 Video: Foundation Models for Synchronized Video and Audio Generation（Kandinsky 6.0 Video：用于同步视频与音频生成的基础模型）
[02:49] 🌳 The Trinity:Capability-Driven Recursive Self-Improvement for Multimodal Agents（The Trinity：多模态智能体的能力驱动递归自我改进）
[03:59] 🦾 PDRVLA: A Vision-Language-Action Model with Physical Dynamics Representations（PDRVLA：具有物理动力学表征的视觉—语言—动作模型）
[05:09] 🧭 The Teacher Is a Direction, Not a Destination: Extrapolating RL-Induced Representation Residuals in On-Policy Distillation（教师是方向，而非终点：在同策略蒸馏中外推强化学习诱导的表征残差）
[06:21] 🔍 False Frontiers: Diagnosing and Mitigating Co-Cheating in Self-Evolving Search Agents（虚假前沿：诊断与缓解自我进化搜索智能体中的共同作弊）
[07:32] ⚖️ Jeva: System One Models from First Principles（Jeva：从第一性原理构建系统一模型）
[08:43] 🧠 MemT-1.0: Towards Memory-Native Evolution（MemT-1.0：迈向记忆原生进化）
[09:53] 🤖 Has GPT-6-Astra Achieved Embodied Intelligence?（GPT-6-Astra已经实现具身智能了吗？）
[11:03] 🎨 UniEvo-VL: An On-policy Self-Distillation Training Recipe for Multimodal Model Self-improvement（UniEvo-VL：用于多模态模型自我改进的同策略自蒸馏训练配方）
[播客论文目录配图]
【关注我们】
您还可以在以下平台找到我们，获得播客内容以外更多信息
小红书: AI速递