2026.08.26 | 将标注视为轨迹以加速视频强化学习；微信多模态嵌入模型刷新纪录

【赞助商】OpenClaw快报每天五分钟，听听 OpenClaw 快报，带你了解最新动态和业内讨论传送门 https://www.xiaoyuzhoufm.com/podcast/6a1732a2dffa135d0ab5ef43【目录】本期的 15 篇论文如下：[00:32] 🎯 Annotations as Rollouts: Efficient and Scalable Reinforcement Learning for Video MLLMs（将标注视为轨迹：高效可扩展的视频多模态大语言模型强化学习）[01:25] 🧲 WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report（WeMM-Embedding：微信多模态嵌入技术报告）[02:17] 🔧 AutoSaddler: Automatic Harness Optimization with Durable Updates from Agent Execution Traces（AutoSaddler：基于智能体执行轨迹的自动框架优化与持久更新）[03:17] 🎯 On-Policy Self-Distillation in Diffusion Models（扩散模型中的同策略自蒸馏）[04:02] 🛡 CyberFactory: Scaling Cyber Security Capabilities with Instances from the Wild（CyberFactory：利用现实世界实例规模化网络安全能力）[05:00] 🧠 Recursive Experiential-Working Memory Evolution for Long-Horizon Agent Harnesses（面向长时程智能体框架的递归经验-工作记忆演化）[05:53] 🎯 Best Practice Critic Optimization（最佳实践评论家优化）[06:45] 🎯 On-policy Distillation with Verifiable Reward（基于可验证奖励的在线策略蒸馏）[07:42] 🕶 From Seeing to Acting: Smart Glasses as First-Person Intelligence Platforms（从看见到行动：智能眼镜作为第一人称智能平台）[08:41] 🎮 Game2World Engine: Unlocking In-the-Wild Gameplay Videos for World Model Training（Game2World引擎：解锁真实场景游戏视频以训练世界模型）[09:34] 📏 Length-Adaptive Decoding for Masked Diffusion Machine Translation（掩码扩散机器翻译的长度自适应解码）[10:27] 🎬 LAION-BVD: A 10-Million-Hour Open Video Dataset for Multimodal Pre-training（LAION-BVD：面向多模态预训练的千万小时开放视频数据集）[11:21] 🔁 Meta$^n$: Recursive Self-Improvement through Emergent Depth（Meta^n：通过涌现深度实现递归自我改进）[12:13] 🤖 CAFE: Self-Improving Search Agents Need Co-Evolving Feedback（CAFE：自我改进的搜索智能体需要协同演化的反馈）[13:14] 🔮 Latent Action as Intention Enables Efficient Future Imagination for World Action Models（以潜在动作作为意图，实现世界动作模型的高效未来想象）【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速递在小宇宙查看该单集文稿