2026.08.27 | 双脑记忆让语音助手实时又准确；科学工作流多数模型难善终

【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：[00:31] 🧠 VoiceMem: Streaming Dual-Brain Memory for Real-Time Interaction（VoiceMem：面向实时交互的流式双脑记忆）[01:30] 🧪 FrontierChallenge: Evaluating Scientific Workflow Completion（前沿挑战：评估科学工作流完成度）[02:29] 🎬 VGI-Bench: Probing Visual Intelligence in Video Generation Models（VGI-Bench：探究视频生成模型的视觉智能）[03:32] 🚀 WarpSAC: Towards the Pinnacle of Scalable Off-policy RL by Rethinking Exploration and Exploitation（WarpSAC：重思探索与利用，迈向可扩展离策略强化学习的巅峰）[04:27] ⚙ JIT-Agent: Scaling Harness Intelligence via Just-in-Time Harness Evolution（JIT-Agent：通过即时框架演化实现框架智能的规模化扩展）[05:20] 🧠 VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning（VBVR-Pro：可扩展且可验证的原生视觉推理套件）[06:15] 🎛 D$^3$-MOPD: Adaptive Dynamic Domain ScheDuling for Efficient Multi-Teacher Distillation（D³-MOPD：面向高效多教师蒸馏的自适应动态领域调度）[07:22] 🧠 Is Next-Chunk Reasoning RL Really Better than SFT? Revisiting Training Strategies under no-CoT Data（下一块推理强化学习真的比SFT更好吗？重新审视无CoT数据下的训练策略）[08:26] 🎯 Agent-G$^2$: Gaussian Guidance for Agentic Reinforcement Learning（Agent-G²：面向智能体强化学习的高斯引导）[09:13] 🎬 Long-Horizon Audio-Visual Generation for Persistent Stories and Interactive Worlds（面向持久故事与交互世界的长时程音视频生成）[10:19] ⚖ Open-MOPD: Diagnosing and Fixing Capability Imbalance in Multi-Teacher On-Policy Distillation（Open-MOPD：多教师同策略蒸馏中能力失衡的诊断与修复）[11:26] 🤖 StreamPI: Streaming Multimodal Temporal Modeling for Vision-Language-Action Models（StreamPI：面向视觉-语言-动作模型的流式多模态时序建模）[12:29] 🎬 Video-IFBench: Evaluating Instruction Following of Multimodal LLMs in Video Understanding Scenarios（视频-IFBench：评估多模态大语言模型在视频理解场景中的指令跟随能力）[13:30] 🧠 Code World Model: Coding Agent as World Brain（代码世界模型：代码智能体作为世界大脑）[14:25] 🎯 V-Rubrics: Visual Faithfulness via Rubric-Based Reinforcement Learning（V-Rubrics：基于评分标准的强化学习实现视觉忠实性）【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