HuggingFace 每日AI论文速递

HuggingFace 每日AI论文速递 的全部节目

共 738 集。

2026.11.06 | 视觉规划整块解码;借兄弟框架练智能体

2026.11.06 | 视觉规划整块解码;借兄弟框架练智能体

HuggingFace 每日AI论文速递

⏱️ 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) [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

8 分钟 23 次播放 2天前

【月末特辑】10月最火AI论文 | 把经验变成预见;让音画同步生成

【月末特辑】10月最火AI论文 | 把经验变成预见;让音画同步生成

HuggingFace 每日AI论文速递

⏱️ 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] 【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

12 分钟 25 次播放 2天前

2026.11.05 | 动作读取视觉层级;分钟级游戏世界数据

2026.11.05 | 动作读取视觉层级;分钟级游戏世界数据

HuggingFace 每日AI论文速递

⏱️ Highlights [00:27] 🦾 From Pixels to Actions - Towards Native Vision-Language-Action Policies(从像素到动作——迈向原生视觉语言动作策略) [01:05] 🎮 GameVerse: A Minute-Scale Gameplay Dataset for Long-Horizon Interactive World Modeling(GameVerse:面向长时域交互世界建模的分钟级游戏数据集) [01:41] 💬 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) [02:17] 🔬 FrontierPhysics: Evaluating Agents for End-to-End Physics Research(FrontierPhysics:评估端到端物理研究智能体) [02:57] 🧭 What Does Multi-Turn Reinforcement Learning Really Improve in LLM Agents?(多轮强化学习究竟改善了大语言模型智能体的什么能力?) [03:36] 🏭 PyRUA-DataFarm: LLM Agent as a Cost-Efficient Teleoperator for Real-Ready Robot Data(PyRUA-DataFarm:以大语言模型智能体作为低成本遥操作员,生成可用于实机的机器人数据) [04:15] 🎭 EmoReward: Self-Evolving Reward Calibration for Emotional Video Generation RL(EmoReward:用于情绪视频生成强化学习的自演化奖励校准) [04:52] 🎙️ StreamDuo: A Live Commentator and a Research Agent for Unseen Games(StreamDuo:面向未见游戏的实时解说员与研究智能体) [05:33] 🧩 Solv3R: 3D Looped Transformer as a Multi-view Solver(Solv3R:作为多视图求解器的三维循环Transformer) [06:13] 🤝 Human-to-Robot Transfer via Bridging Representation and Action Space in VLAs(通过桥接VLA的表征与动作空间实现人到机器人的迁移) [06:51] 🖼️ VA-TDM: A Unified View for Improving Few-Step Diffusion Models by Velocity Adversarial Distillation(VA-TDM:通过速度对抗蒸馏改进少步扩散模型的统一视角) [07:31] 💾 MUON-RT Reusing the Teacher's Trajectory for Momentum-Free Muon for LLM Self-Distillation(MUON-RT:复用教师轨迹,为大语言模型自蒸馏实现无动量Muon) [08:09] 🏠 AnchorComplete: Recovering Complete Scene Meshes from Partial Point Clouds(AnchorComplete:从局部点云恢复完整场景网格) [08:48] 🧠 VideoMemBench: How Well Do MLLMs Remember in Video Conversations?(VideoMemBench:多模态大语言模型在视频对话中记得有多好?) [09:24] 🌿 SpecOPD: Branch-Parallel On-Policy Distillation for Speculative Decoding(SpecOPD:用于推测解码的分支并行同策略蒸馏) [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

10 分钟 31 次播放 3天前

2026.11.04 | 为模型与策略选路;让模拟来访者自然表达

2026.11.04 | 为模型与策略选路;让模拟来访者自然表达

HuggingFace 每日AI论文速递

⏱️ Highlights [00:27] 🧭 Route Anything: A Study of Model and Policy Routing for General-Purpose AI Systems(Route Anything:面向通用AI系统的模型与策略路由研究) [01:03] 💬 Words Caught in the Heart: Simulating Person-Specific Expression for Self-Opaque Clients in Psychotherapy(困在心中的话:为心理治疗中难以理解自身体验的来访者模拟个体化表达) [01:41] 🧠 Think Less, Locally: Local Preference Learning for Reasoning Compression(局部少想一点:用于推理压缩的局部偏好学习) [02:16] 🎬 MoviEdit: Long-form Multi-Shot Video Editing Made Easy(MoviEdit:让长篇多镜头视频编辑更轻松) [02:53] 🎞️ Behind Video Generation: Observations and Insights on Multimodal Understanding from Kling(视频生成的背后:来自Kling的多模态理解观察与洞见) [03:30] 🦾 DreamX: Video Diffusion Model is a Universal Latent Action Learner(DreamX:视频扩散模型是一种通用潜动作学习器) [04:05] 🤖 RoboColosseum: Evaluating Physical Intelligence at Scale In-The-Wild(RoboColosseum:在真实开放环境中规模化评估物理智能) [04:42] 🔎 Factorized MLLM Embeddings for Composed Image Retrieval(用于组合式图像检索的因子化多模态大语言模型嵌入) [05:19] 🛠️ Axion 1.0: Open Agent Foundation Models, Simplified(Axion 1.0:化繁为简的开放智能体基础模型) [05:54] 🔗 ToolSpace: Scaling Tool-Centric Environment Synthesis for Long-Horizon Agents(ToolSpace:为长程智能体扩展以工具为中心的环境合成) [06:32] 🗂️ YANAMI: A Large-Scale Multimodal Dataset and Benchmark for Multiturn Stateful Interaction(YANAMI:用于多轮有状态交互的大规模多模态数据集与基准) [07:10] 🤝 EvoTeam: Multi-Agent Collaboration via Evolving Teams(EvoTeam:通过演化团队实现多智能体协作) [07:47] 📽️ VidUEU-Agent: A Data-Curation Agent for Multimodal Understanding, Editing, and Unified Tasks(VidUEU-Agent:面向多模态理解、编辑与统一任务的数据策展智能体) [08:26] 🌐 WebHarbor: Docking Real Websites for Evolving GUI Agent Environments(WebHarbor:将真实网站接入可演进的GUI智能体环境) [09:04] ⚖️ ParetoSaddler: Pareto-Guided Optimization of Agent Harnesses for Quality and Cost(ParetoSaddler:以帕累托方法引导智能体运行框架的质量与成本优化) [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

10 分钟 54 次播放 4天前

2026.11.03 | 视频生成波前流水线;视频智能体的反馈边界

2026.11.03 | 视频生成波前流水线;视频智能体的反馈边界

HuggingFace 每日AI论文速递

⏱️ Highlights [00:26] 🌊 Wave Forcing: Towards Speed-of-Light Streaming Video Generation(Wave Forcing:迈向光速的流式视频生成) [01:01] 🎬 Video Generation Meets Agent Harness: Agentic Video Generation, Agentic World Modeling and Recursive Self-Improvement(当视频生成遇上智能体运行框架:智能体式视频生成、智能体式世界建模与递归自我改进) [01:40] 🤝 CoworkOS:Scaling Agent Coworkers for Real-world Automation(CoworkOS:扩展面向现实世界自动化的智能体同事) [02:18] 🦾 Democratizing Robot-Use Agents: A Unified Harness with Open Models(让机器人使用智能体更普及:采用开放模型的统一运行框架) [02:55] 🖥️ CUA-Master: Scaling Computer-use Agents through Open-World Recursive Improvements(CUA-Master:通过开放世界递归改进扩展计算机使用智能体) [03:33] 🧭 NorthCUA Technical Report: Turbocharging Computer-Use Agents through Experience at Scale(NorthCUA 技术报告:通过规模化经验加速计算机使用智能体) [04:13] ↩️ Lost in Recovery: Demystifying Recovery Behavior of Computer-Use Agents via Goal-Oriented Action Replay(迷失于恢复:通过目标导向动作重放揭示计算机使用智能体的恢复行为) [04:51] 👁️ Reviso: Not All Visual Evidence Deserves Equal Attention in Video Captioning(Reviso:视频描述中,并非所有视觉证据都值得同等关注) [05:30] 🧩 From Fragmentation to Fusion: A Survey and Roadmap for Omnimodal Embeddings(从碎片化到融合:全模态嵌入的综述与路线图) [06:07] 💻 CrossSWE: Benchmarking Cross-Repository Joint Development for Coding Agents(CrossSWE:评测编程智能体的跨仓库联合开发) [06:48] 📷 PhotoGuider: Composition-Aware Cropping and 360^{circ} View Framing with Explainable Photographic Assessments(PhotoGuider:结合可解释摄影评估的构图感知裁剪与360°视角取景) [07:25] 🙋 Avatar Intelligence: Amplifying Human Agency Through Persistent Personal Agents(Avatar Intelligence:通过持久个人智能体增强人的自主行动能力) [08:05] 🔢 Diagnosing the Reference Gap: What Visual Scaffolds Can and Cannot Fix in Multimodal Reasoning(诊断指代鸿沟:视觉支架在多模态推理中能与不能修复什么) [08:42] 📑 DecisionRank: On-Policy Distillation for Decision-Model Rerankers(DecisionRank:面向决策模型重排器的在策略蒸馏) [09:21] 🔎 DeFT-RAG: Decomposing Multi-Hop Questions into Self-Contained Sub-Questions with Reusable Answers(DeFT-RAG:将多跳问题分解为答案可复用的自足子问题) [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

10 分钟 81 次播放 5天前

2026.11.02 | 视频先验统一生图;自博弈内化编排技能

2026.11.02 | 视频先验统一生图;自博弈内化编排技能

HuggingFace 每日AI论文速递

⏱️ Highlights [00:25] 🎞️ FrameForge: Harnessing Priors of Video Foundation Models for Unified Image Generation(FrameForge:利用视频基础模型先验实现统一图像生成) [01:04] 🔁 R^2Orch: Recursive Self-Improvement for Agent Orchestration via Self-Play within a Skill-Internalization Loop(R^2Orch:在技能内化循环中通过自博弈实现智能体编排的递归自我改进) [01:42] 🧠 Does Scaling Toward AGI Depend on What System-1 Lets System-2 Execute?(迈向 AGI 的规模扩展,取决于 System-1 允许 System-2 执行什么吗?) [02:20] 🤖 REA: A Routed Embodied Agent Runtime for Asynchronous Brain-Cerebellum Control(REA:面向异步大脑—小脑控制的路由式具身智能体运行时) [02:58] 🎙️ Apriel Voice 27B Preview: An Open Model for Speech, Reasoning, and Tool Use(Apriel Voice 27B 预览版:面向语音、推理与工具使用的开放模型) [03:37] 🎮 Wizard: Manipulate Any World in Real Time via Agentic Control(Wizard:通过智能体控制实时操纵任意世界) [04:14] 💭 Latent Reasoning in Continuous Space for Unified Multimodal Models(统一多模态模型在连续空间中的潜在推理) [04:51] 🔭 HiFOR: Hierarchical Foresight with Action-Guided World Grounding for Vision-Language-Action Model(HiFOR:面向视觉—语言—动作模型的分层前瞻与动作引导世界信息锚定) [05:31] 🔎 WeFair: Fidelity-Aware Alignment from Human Feedback for Personalized Query Rewriting in Short-Video Search(WeFair:面向短视频搜索个性化查询改写的保真度感知人类反馈对齐) [06:11] ⚡ OSWAM: An Effective World Action Model with One-Step Action Generation(OSWAM:具备单步动作生成能力的高效世界动作模型) [06:49] 🧵 ReLift: Dense 3D Tracking as Lifted Trajectory Repair(ReLift:将稠密三维跟踪视为提升后轨迹的修复) [07:27] 🤝 CEPO: A General Framework for Improving Prompt Optimization in Multi-Agent Systems(CEPO:改进多智能体系统提示词优化的通用框架) [08:06] 🕵️ Venus-DefakerOne2: A Vision-Forensics Foundation Model with Broader Coverage(Venus-DefakerOne2:覆盖范围更广的视觉取证基础模型) [08:43] 🦾 CaPtain: A Pipeline for Post-Training Code-as-Policy Robot Agents(CaPtain:代码即策略机器人智能体的后训练流程) [09:22] 🧭 Probing Spatial State Representations in Visual Foundation Models(探测视觉基础模型中的空间状态表征) [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

10 分钟 59 次播放 6天前

2026.10.29 | 扩散模型如何分功劳;嘈杂声场锁定目标声音

2026.10.29 | 扩散模型如何分功劳;嘈杂声场锁定目标声音

HuggingFace 每日AI论文速递

⏱️ Highlights [00:27] 🧠 DTCA: Denoising Token Credit Assignment for Reinforcement Learning in Diffusion Language Models(DTCA:用于扩散语言模型强化学习的去噪词元信用分配) [01:19] 🎧 Efficient Streaming Audio-Visual Target Speaker Extraction for Real-World Acoustic Scenes(面向真实声学场景的高效流式音视频目标说话人提取) [02:13] 🎬 OmniShowcase: Omnidirectional Subject-Consistent Video Generation from Multi-View Images(OmniShowcase:从多视图图像生成全方位主体一致的视频) [03:04] 🤖 Sensorimotor Alignment: A Platonic Proxy for Embodied Policy Success(感觉运动对齐:具身策略成功表现的柏拉图式代理指标) [03:56] ⚙️ TAO: Tool-Aware Joint Scheduling for LLM-Based Agentic Serving(TAO:面向基于大语言模型的智能体服务的工具感知联合调度) [04:53] 💻 RealCLI: Toward a Unified Evaluation of Human-Agent Collaboration for CLI Agents(RealCLI:迈向命令行智能体的人机协作统一评估) [05:43] 🏦 TauIndianBankBench: Procedure-Aware, Action-Oriented Evaluation of Tool-Using Conversational Agents(TauIndianBankBench:面向工具使用型对话智能体的流程感知、行动导向评估) [06:36] 📚 LongZero: Enhancing Long-Context Reasoning in LLMs from Zero Data(LongZero:从零数据增强大语言模型的长上下文推理) [07:27] 🔗 CausGround: Causal Interaction Grounding for Adaptive Embodied Planning(CausGround:面向自适应具身规划的因果交互落地) [08:18] 🦾 HuGe: Scaling Humanoid Generalist Vision-Language-Action Models with Egocentric Experience(HuGe:利用第一视角经验扩展人形通用视觉—语言—动作模型) [09:13] 🔭 OmniSpectra: A Unified Foundation Model for Universal Spectra Representation Learning(OmniSpectra:用于通用光谱表征学习的统一基础模型) 【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

10 分钟 69 次播放 1周前

2026.10.23 | MLLM潜变量赋能电影视频生成;开放网络搜索基准暴露瓶颈

2026.10.23 | MLLM潜变量赋能电影视频生成;开放网络搜索基准暴露瓶颈

HuggingFace 每日AI论文速递

【目录】 本期的 15 篇论文如下: [00:24] 🎬 Making MLLM Latents Matter: Factor-Aware Predictive Learning for Cinematic Video Generation(让MLLM潜变量发挥作用:面向电影级视频生成的因子感知预测学习) [01:07] 🔍 Deep Search in Real-World Web Environments(真实世界网络环境中的深度搜索) [01:48] 👁 WeVisOne-VL: Unified Visual Perception from Objects to Pixels(WeVisOne-VL:从物体到像素的统一视觉感知) [02:34] 🧩 Editing Images into Reusable Layers via Compositional Edit-Prior Distillation(通过组合式编辑先验蒸馏将图像编辑为可复用图层) [03:15] 🤖 IQuest-Q1: Advancing Foundation Capabilities for Agentic CLI Systems(IQuest-Q1:提升面向智能体 CLI 系统的基础能力) [03:58] 🤖 Toward Recursive Self-Improvement in Physical AI(迈向物理人工智能中的递归自我改进) [04:38] 🧠 Deep Fusion Memory: A Chunk-Level Parametric Memory for Large Language Models(深度融合记忆:面向大语言模型的块级参数化记忆) [05:27] 🔍 What Generation Knows: Unlocking Fine-Grained Understanding in Unified Multimodal Models(生成知道什么:解锁统一多模态模型中的细粒度理解) [06:18] 🌍 LaLa-World: Scaling Latent World Models with Natural Language Actions(LaLa-World:以自然语言动作扩展潜在世界模型) [07:11] 🧩 Meta Expert: Cross-Layer Expert Sharing for Storage- and Retrieval-Efficient MoE(Meta Expert:面向存储与检索高效的跨层专家共享 MoE) [08:05] 🎧 Heartbeat Thinking: Speculative Reasoning and Tool Execution While Listening in Realtime Voice Agents(心跳思考:实时语音代理在聆听过程中的推测性推理与工具执行) [08:47] 🎛 Policy-Mask: Budget-Aware Adaptation of Diffusion Features to Discriminative Tasks(Policy-Mask:面向判别任务的扩散特征预算感知适配) [09:31] 🎬 Code2Video-Compass: A Comprehensive Benchmark for General-Purpose Code-Based Video Generation across T2V, I2V, and V2V(Code2Video-Compass:面向T2V、I2V和V2V的通用代码视频生成综合基准) [10:16] 🧠 Cola2: Co-Adaptive Hierarchical Language Modeling with Continuous Semantic Compression and Balanced Discrete Generation(Cola2:具有连续语义压缩与平衡离散生成的协同自适应分层语言建模) [11:01] 🎥 Beyond Watching and Searching: Benchmarking Agents for Video-centered Deep Research Reports(超越观看与搜索:面向以视频为中心的深度研究报告的智能体基准测试) 【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

12 分钟 50 次播放 2周前

2026.10.22 | 流式视频评测揭示时序瓶颈;VLM三维建图仍难精准

2026.10.22 | 流式视频评测揭示时序瓶颈;VLM三维建图仍难精准

HuggingFace 每日AI论文速递

【目录】 本期的 15 篇论文如下: [00:25] 🎬 StreamEval: Evaluating Interactive Streaming Video Generation Models(StreamEval:评估交互式流式视频生成模型) [01:08] 🗺 SpatialScout: Can VLM Agents Actively Explore and Map 3D Scenes?(SpatialScout:VLM智能体能否主动探索并构建3D场景地图?) [01:55] 🎞 Looking Ahead: Modeling Future Evolution in Autoregressive Video Generation(展望未来:自回归视频生成中的未来演化建模) [02:42] 🗄 Cache Engineering for Agents(面向智能体的缓存工程) [03:24] 👐 DONIC: Generalist Dexterous Bimanual Tracking Control from Human Demonstrations(DONIC:基于人类演示的通用灵巧双手跟踪控制) [04:11] 🌍 Agent World Model in the Wild: Computer-Use Agent Environment Synthesis(真实环境中的智能体世界模型:计算机使用智能体环境合成) [04:52] 🔍 Spectral-Spatial Interpretation(光谱-空间解释) [05:36] 🧩 PrismaCoder: Pushing the Boundaries of Open Multimodal Code Intelligence through Decomposed Rubric Synthesis(PrismaCoder:通过分解式评分细则合成突破开放多模态代码智能的边界) [06:22] 🎓 Socratic Skill Learning: Interleaving Teaching and Practice for Transferable Agent Skills(苏格拉底式技能学习:交错教学与实践以培养可迁移的智能体技能) [07:07] 🎮 Scaling in Games: Continued Pre-Training For Embodied Agents In Diverse Virtual Worlds(游戏中的规模化:面向多样虚拟世界具身智能体的持续预训练) [07:43] 🤖 AgenticRoboRL: Bringing Coding-Agent Post-Training to Agentic Robotics(AgenticRoboRL:将编程智能体后训练引入智能体机器人) [08:31] 🧠 Memory-Centric Continual Learning for AI Agents(以记忆为中心的AI智能体持续学习) [09:17] 🤖 Multimodal Embodied Agents: A Unified Capability-centric Perspective from Computer-Use to Robot-Use(多模态具身智能体:从计算机使用到机器人使用的统一能力中心视角) [10:00] 🧠 TraceForge: Distilling with Your Own Thinking(TraceForge:用自身思考进行蒸馏) [10:40] 🛡 Right Screen, Wrong Transition: World Models as Verifiers for GUI Agents(正确的屏幕,错误的转移:世界模型作为GUI智能体的验证器) 【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

11 分钟 75 次播放 2周前

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