⏱️ Highlights
[00:25] 🌐 SplatAnything: Gaussian Spacing Normalization for Feed-forward 3DGS across Arbitrary Scenes(SplatAnything:面向任意场景前馈式3DGS的高斯间距归一化)
[01:02] 🧠 P^2-MOPD: Accelerating Multi-Teacher On-Policy Distillation via Parameter Priors(P²-MOPD:通过参数先验加速多教师在策略蒸馏)
[01:43] 🎨 LongBanana: An Expert-Verified Benchmark for Long-Context Multi-Reference Image Synthesis(LongBanana:经专家核验的长上下文多参考图像合成基准)
[02:21] 🔍 Beneath the Surface: What We Overlook When We Talk About Agent Evolution(表象之下:谈论智能体进化时,我们忽略了什么)
[03:00] 🎬 EvoWorld: Towards Out-of-Sight World Evolution in Generative Video Models(EvoWorld:迈向生成式视频模型中的画外世界演化)
[03:39] ⚙️ Fast and Exact Relative-Position Attention via Structure-Aware Kernels(通过结构感知内核实现快速且精确的相对位置注意力)
[04:17] 🎙️ Confucius4-R2T2: A Stable-Prefix Streaming ASR Model for Real Real-Time Transcription(Confucius4-R2T2:面向真正实时转写的稳定前缀流式语音识别模型)
[04:57] 🤝 AgentBaton: Efficient Model Collaboration in Agentic Tasks(AgentBaton:智能体任务中的高效模型协作)
[05:37] 💻 Video-Coder: Reinforcing Agentic Coding for Video Generation(Video-Coder:通过强化智能体编码实现视频生成)
[06:17] 🧩 Exploring Weight-Space Programming: Capabilities, Generalization, and Limitations(探索权重空间编程:能力、泛化与局限)
[06:57] 🏗️ Frontier3DBench: Benchmarking Coding Agents for 3D Creation across Objects, Scenes, and Interactive Open Worlds(Frontier3DBench:跨物体、场景与交互式开放世界的编码智能体三维创作评测)
[07:41] 📷 PREEN: Exemplar-Based Color Style Transfer with Smartphone Editor Presets(PREEN:使用智能手机编辑器预设的示例驱动色彩风格迁移)
[08:18] 📊 LLMs Don't Know What They Know: Benchmarking Temporal Self-Knowledge for Financial Backtesting(大语言模型不知道自己知道什么:面向金融回测的时间自知能力评测)
[09:00] 🔧 AutoCompress: Automated Hardware-Guided Model Compression(AutoCompress:自动化硬件引导模型压缩)
[09:41] 🧱 OmniLatent: Unified Latent for 3D Part Modeling(OmniLatent:用于三维部件建模的统一潜表示)
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小红书: AI速递
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7 Nov 2026
【周末特辑】11月第2周最火AI论文 | 图形智能体的设计空间;错峰去噪生成视频
⏱️ Highlights
[00:31] 🎨 Advances in Agentic Computer Graphics(智能体计算机图形学进展)
[02:23] 🌊 Wave Forcing: Towards Speed-of-Light Streaming Video Generation(Wave Forcing:迈向光速的流式视频生成)
[04:18] 🤖 Are Frontier VLM Agents Ready to Be Robot Generalists? An Empirical Study with the Embodied Agent Arena(前沿VLM智能体准备好成为机器人通才了吗?基于Embodied Agent Arena的实证研究)
[06:20] 🛠️ CoworkOS:Scaling Agent Coworkers for Real-world Automation(CoworkOS:扩展智能体同事以实现真实世界自动化)
[08:28] 🎬 Turns Matter: Advancing Streaming Video RL via Turn-Level Credit(轮次很重要:通过轮级信用分配推进流式视频强化学习)
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小红书: AI速递
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6 Nov 2026
2026.11.06 | 视觉规划整块解码;借兄弟框架练智能体
⏱️ Highlights
[00:22] 🧭 VFlash: Fast, Accurate Visual Planning via Flash Primitive Decoding(VFlash:通过闪速图元解码实现快速、准确的视觉规划)
[00:54] 🛠️ Harness-S: Learning from Sibling Harnesses for Generalizable Agent Training(Harness-S:向兄弟执行框架学习,实现可泛化的智能体训练)
[01:24] 🎲 Random Is Almost Enough? Stable and Low-Cost Benchmark Compression via BestRand(随机抽样几乎就够了吗?通过 BestRand 实现稳定、低成本的基准压缩)
[01:53] 🎨 TailSteer: Trajectory-Tail Steering for Drift-Resistant Multi-turn Image Editing(TailSteer:通过轨迹尾段引导实现抗漂移的多轮图像编辑)
[02:24] 🖼️ WeLM-Image: A Unified Image Generation Model towards Visual Intelligence(WeLM-Image:迈向视觉智能的统一图像生成模型)
[02:59] 🤖 SLA: Scaling Spatial-Language-Action Model via Continual Pre-training(SLA:通过持续预训练扩展空间—语言—动作模型)
[03:34] 🧠 EvoMemState: Evolving Memory State for Personal Agents(EvoMemState:为个人智能体演化记忆状态)
[04:08] 🔎 VisSearch-Bench: Evaluating Long Horizon Visual Search in Multimodal Agents(VisSearch-Bench:评估多模态智能体的长程视觉搜索)
[04:38] ⚖️ Towards Foundation Decision Models: Drex(迈向基础决策模型:Drex)
[05:08] 🌉 On the Opportunities and Challenges of Prefill-to-Autoregressive Cross-Model Transfer(论预填充到自回归的跨模型迁移:机遇与挑战)
[05:37] 👤 EDGAR: Efficient Diffusion-Driven Gaussian Avatar Refinement via Synthetic Failure(EDGAR:通过合成失败实现高效的扩散驱动高斯头像细化)
[06:05] 📝 HeLM: Hierarchical Explicit Language Memory for Non-Markovian Manipulation(HeLM:用于非马尔可夫操作的分层显式语言记忆)
[06:37] 🎬 Future Representation Distillation for Imagination-free World Action Models(用于免想象世界动作模型的未来表征蒸馏)
[07:11] 🤝 From Autonomous Agents to Cognitive Symbionts: Toward AI-Augmented Human Intelligence(从自主智能体到认知共生体:迈向 AI 增强的人类智能)
[07:42] 🎧 Decode Before You Hear: Speculative Listening for Chunk-Interleaved Full-Duplex Speech Language Models(听到之前先解码:面向分块交错全双工语音语言模型的推测式聆听)
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小红书: AI速递
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