HuggingFace 每日AI论文速递 - 节目列表

2026.05.22 | 大模型内化地理空间;判别性令牌优化推理

2026.05.22 | 大模型内化地理空间;判别性令牌优化推理

HuggingFace 每日AI论文速递

【目录】 本期的 15 篇论文如下: [00:25] 🚌 TransitLM: A Large-Scale Dataset and Benchmark for Map-Free Transit Route Generation(TransitLM: 面向无地图公交路线生成的大规模数据集与基准) [01:21] 🎯 DelTA: Discriminative Token Credit Assignment for Reinforcement Learning from Verifiable Rewards(DelTA:面向可验证奖励强化学习的判别性令牌信用分配) [02:15] 🤖 $π$-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows(π-Bench:评估长时工作流中的主动式个人助理代理) [03:04] 🤔 Perception or Prejudice: Can MLLMs Go Beyond First Impressions of Personality?(感知还是偏见:多模态大语言模型能否超越对个性的第一印象?) [03:51] 🔥 Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps(全注意力回归:在百步训练内将全注意力迁移至稀疏注意力) [04:35] 🤖 ACC: Compiling Agent Trajectories for Long-Context Training(ACC:为长上下文训练编译智能体轨迹) [05:35] 🧊 PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects(PhysX-Omni:面向刚体、可变形体和关节物体的统一仿真就绪物理3D生成) [06:37] 🧠 LatentOmni: Rethinking Omni-Modal Understanding via Unified Audio-Visual Latent Reasoning(LatentOmni:通过统一音频-视觉潜在推理重新思考全模态理解) [07:37] 🌍 WorldKV: Efficient World Memory with World Retrieval and Compression(世界KV:结合世界检索与压缩的高效世界记忆) [08:22] 📊 Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning(Spreadsheet-RL:通过强化学习推进大型语言模型智能体在真实电子表格任务中的应用) [09:27] 🎥 FlowLong: Inference-time Long Video Generation via Manifold-constrained Tweedie Matching(FlowLong:基于流形约束Tweedie匹配的推理时长视频生成) [10:35] 🧠 SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation(SpaceDG:视觉退化下的空间智能基准测试) [11:35] 🎯 Maestro: Reinforcement Learning to Orchestrate Hierarchical Model-Skill Ensembles(Maestro:强化学习编排层次化模型-技能集成) [12:29] 🚗 Sensor2Sensor: Cross-Embodiment Sensor Conversion for Autonomous Driving(传感器到传感器:面向自动驾驶的跨本体传感器转换) [13:21] 🎥 Q-ARVD: Quantizing Autoregressive Video Diffusion Models(Q-ARVD:量化自回归视频扩散模型) 【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 2026.05.22 | 大模型内化地理空间;判别性令牌优化推理

14分钟
99+
1个月前
2026.05.21 | Mega-ASR降噪减幻觉;Video2GUI数据预训练提效

2026.05.21 | Mega-ASR降噪减幻觉;Video2GUI数据预训练提效

HuggingFace 每日AI论文速递

【目录】 本期的 15 篇论文如下: [00:23] 🎤 Mega-ASR: Towards In-the-wild^2 Speech Recognition via Scaling up Real-world Acoustic Simulation(Mega-ASR:通过扩展真实世界声学模拟实现野外环境语音识别) [01:22] 🎬 Video2GUI: Synthesizing Large-Scale Interaction Trajectories for Generalized GUI Agent Pretraining(Video2GUI:合成大规模交互轨迹以实现通用型GUI代理预训练) [02:11] 🎬 Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos(增强无训练无限帧生成以实现一致的长视频) [03:04] 🚀 You Only Need Minimal RLVR Training: Extrapolating LLMs via Rank-1 Trajectories(你仅需极简的RLVR训练:通过秩-1轨迹外推大语言模型) [03:50] 🗜 OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond(OScaR:面向大语言模型及更广领域的极致KV缓存量化的奥卡姆剃刀) [04:39] 🔧 IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools(IndusAgent:利用智能工具增强开放词汇工业异常检测) [05:36] 🔊 A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook(大型音频语言模型综述:泛化、可信度与展望) [06:35] 🤝 It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs(双管齐下:面向大语言模型语境完整性的互补式自蒸馏框架) [07:26] 📈 Toto 2.0: Time Series Forecasting Enters the Scaling Era(Toto 2.0:时间序列预测进入规模化时代) [08:20] ⚡ Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs(混合量化:面向智能体大语言模型的量化预填充与精确解码) [09:25] 🧠 Generative Recursive Reasoning(生成式递归推理) [10:29] 🎬 CutVerse: A Compositional GUI Agents Benchmark for Media Post-Production Editing(CutVerse:面向媒体后期制作编辑的组合式GUI智能体基准) [11:22] 🖼 Uni-Edit: Intelligent Editing Is A General Task For Unified Model Tuning(Uni-Edit:智能编辑作为统一模型调优的通用任务) [12:08] 🧠 LLMEval-Logic: A Solver-Verified Chinese Benchmark for Logical Reasoning of LLMs with Adversarial Hardening(LLMEval-Logic:一个求解器验证的中文逻辑推理基准测试,具备对抗性强化) [13:07] ⚡ HRM-Text: Efficient Pretraining Beyond Scaling(HRM-Text:超越规模的高效预训练) 【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

14分钟
92
1个月前
2026.05.20 | 反自蒸馏优化推理;可验证环境测评智能体

2026.05.20 | 反自蒸馏优化推理;可验证环境测评智能体

HuggingFace 每日AI论文速递

【目录】本期的 15 篇论文如下:[00:24] 🧠 Anti-Self-Distillation for Reasoning RL via Pointwise Mutual Information(基于点互信息的反自蒸馏用于推理强化学习)[01:08] 🖥 OpenComputer: Verifiable Software Worlds for Computer-Use Agents(OpenComputer:为计算机使用智能体构建可验证的软件世界)[01:53] 🧠 GoLongRL: Capability-Oriented Long Context Reinforcement Learning with Multitask Alignment(GoLongRL:面向能力的长上下文强化学习与多任务对齐)[02:49] 🔬 Process Rewards with Learned Reliability(具有学习可靠性的过程奖励模型)[03:44] 🤖 AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration(AutoResearchClaw:基于人类-人工智能协作的自我强化自主研究)[04:48] 🎭 When Vision Speaks for Sound(当视觉为声音代言)[05:50] 🏭 EnvFactory: Scaling Tool-Use Agents via Executable Environments Synthesis and Robust RL(EnvFactory:通过可执行环境合成与鲁棒强化学习扩展工具使用型智能体)[06:45] 🎬 CogOmniControl: Reasoning-Driven Controllable Video Generation via Creative Intent Cognition(CogOmniControl: 基于推理驱动的可控视频生成与创意意图认知)[07:40] 🎯 Active Learners as Efficient PRP Rerankers(主动学习器作为高效的成对排序提示重排序器)[08:24] 🎥 Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos(Artifact-Bench:评估多模态大语言模型在检测与评估AI生成视频伪影方面的能力)[09:14] 🎬 Aurora: Unified Video Editing with a Tool-Using Agent(Aurora:使用工具型代理的统一视频编辑框架)[10:12] 🎯 CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization(对比证据策略优化:基于强化学习与可验证奖励的自蒸馏方法)[11:01] 📱 OmniGUI: Benchmarking GUI Agents in Omni-Modal Smartphone Environments(OmniGUI:在全模态智能手机环境中评估GUI代理的基准测试)[11:51] 🎬 MSAVBench: Towards Comprehensive and Reliable Evaluation of Multi-Shot Audio-Video Generation(MSAVBench:迈向全面且可靠的多镜头音视频生成评估)[12:44] 🎥 Video Models Can Reason with Verifiable Rewards(视频模型可通过可验证奖励进行推理)【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

14分钟
99+
1个月前
2026.05.19 | 长视频生成提速降显存;轻量多模态模型超越大参数模型

2026.05.19 | 长视频生成提速降显存;轻量多模态模型超越大参数模型

HuggingFace 每日AI论文速递

【目录】本期的 15 篇论文如下:[00:23] 🎬 LongLive-2.0: An NVFP4 Parallel Infrastructure for Long Video Generation(LongLive-2.0:用于长视频生成的NVFP4并行基础设施)[01:17] 🎨 Lance: Unified Multimodal Modeling by Multi-Task Synergy(Lance:通过多任务协同实现统一多模态建模)[02:24] 🤖 AI for Auto-Research: Roadmap & User Guide(人工智能自动研究:路线图与用户指南)[03:26] 🛠 SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution(SkillsVote:从收集、推荐到演化的智能体技能全生命周期治理)[04:20] 🎬 KVPO: ODE-Native GRPO for Autoregressive Video Alignment via KV Semantic Exploration(KVPO:基于KV语义探索的ODE原生GRPO自回归视频对齐方法)[05:18] 🏠 Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis(代码即房间:通过智能体代码合成从俯视图生成三维房间)[06:15] 🤖 OProver: A Unified Framework for Agentic Formal Theorem Proving(OProver:面向智能体形式定理证明的统一框架)[07:14] ⚡ Post-Trained MoE Can Skip Half Experts via Self-Distillation(通过自蒸馏实现后训练MoE跳过半数专家)[07:57] 🎥 LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMs(LiteFrame:高效视觉编码器解锁视频大语言模型中的帧缩放)[08:47] 🛑 Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models(当推理收敛时停止:面向推理模型的语义保持型早停方法)[09:42] 🔀 Where Should Diffusion Enter a Language Model? Geometry-Guided Hidden-State Replacement(扩散应进入语言模型的何处?基于几何引导的隐状态替换)[10:39] 🧠 Model-Adaptive Tool Necessity Reveals the Knowing-Doing Gap in LLM Tool Use(模型自适应工具必要性揭示大语言模型工具使用中的知行差距)[11:40] 🛡 StableVLA: Towards Robust Vision-Language-Action Models without Extra Data(稳定视觉-语言-动作模型:无需额外数据实现鲁棒性)[12:43] ⚡ CompactAttention: Accelerating Chunked Prefill with Block-Union KV Selection(紧凑注意力:通过块联合KV选择加速分块预填充)[13:41] 🧪 From Runnable to Shippable: Multi-Agent Test-Driven Development for Generating Full-Stack Web Applications from Requirements(从可运行到可交付:面向全栈Web应用生成的多智能体测试驱动开发)【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

15分钟
71
1个月前
2026.05.18 | 人类视频炼物理常识;文档问答要查原文

2026.05.18 | 人类视频炼物理常识;文档问答要查原文

HuggingFace 每日AI论文速递

【目录】本期的 15 篇论文如下:[00:23] 🧠 PhysBrain 1.0 Technical Report(PhysBrain 1.0 技术报告)[00:56] 🔍 CiteVQA: Benchmarking Evidence Attribution for Trustworthy Document Intelligence(CiteVQA:为可信文档智能建立证据归因基准)[01:45] 🤖 MMSkills: Towards Multimodal Skills for General Visual Agents(MMSkills:面向通用视觉智能体的多模态技能)[02:35] 👗 FashionChameleon: Towards Real-Time and Interactive Human-Garment Video Customization(FashionChameleon:面向实时且交互式的人体-服装视频定制)[03:20] 🦾 DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo(DexJoCo:面向任务型灵巧操作的MuJoCo基准测试与工具包)[04:19] 🔮 Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation(学会预见:揭示在线策略蒸馏的解锁效率)[04:54] 🖼 InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation(InsightTok:改进自回归图像生成中离散标记化的文本和人脸保真度)[05:48] 🧠 Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding(通过协作式逐步多教师解码蒸馏长链思维推理)[06:44] ⚡ Flash-GRPO: Efficient Alignment for Video Diffusion via One-Step Policy Optimization(Flash-GRPO:基于单步策略优化的高效视频扩散对齐方法)[07:29] 🧭 Nudging Beyond the Comfort Zone: Efficient Strategy-Guided Exploration for RLVR(超越舒适区的助推:用于RLVR的高效策略引导探索)[08:10] 🎮 ReactiveGWM: Steering NPC in Reactive Game World Models(反应式游戏世界模型:在反应性游戏世界中操控非玩家角色)[08:46] ⚖ Hölder Policy Optimisation(赫尔德策略优化)[09:36] 🧠 Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution(Solvita:通过智能体进化增强大型语言模型在竞赛编程中的能力)[10:22] 🌐 CM-EVS: Sparse Panoramic RGB-D-Pose Data for Complete Scene Coverage(CM-EVS:用于完整场景覆盖的稀疏全景RGB-D-姿态数据)[11:05] 🎯 PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control(PAGER:弥合点精确几何GUI控制中的语义-执行鸿沟)【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

12分钟
99+
1个月前
2026.05.15 | 30B模型刷奥赛金牌;自蒸馏让3B小模型零外挂超能

2026.05.15 | 30B模型刷奥赛金牌;自蒸馏让3B小模型零外挂超能

HuggingFace 每日AI论文速递

【目录】本期的 15 篇论文如下:[00:23] 🥇 Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling(通过简单且统一的缩放实现金牌级别的奥赛推理)[01:00] 🤖 Self-Distilled Agentic Reinforcement Learning(自蒸馏智能体强化学习)[01:46] 🧠 MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models(MemLens:大型视觉语言模型中多模态长期记忆的基准测试)[02:57] 👁 MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory(MemEye:面向多模态智能体记忆的视觉中心评估框架)[04:00] 🎬 SANA-WM: Efficient Minute-Scale World Modeling with Hybrid Linear Diffusion Transformer(SANA-WM:高效分钟级世界建模的混合线性扩散Transformer)[04:43] 🎬 Causal Forcing++: Scalable Few-Step Autoregressive Diffusion Distillation for Real-Time Interactive Video Generation(因果强制++:面向实时交互式视频生成的可扩展少步自回归扩散蒸馏)[05:21] 🧬 Darwin Family: MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling of Language-Model Reasoning(达尔文家族:基于MRI信任加权进化合并的无训练语言模型推理扩展)[06:19] 🐾 WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation(WildClawBench:面向真实世界长周期智能体评估的基准)[07:11] 🧠 STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?(STALE:LLM代理能否知晓其记忆何时失效?)[08:03] 🧠 Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems(超越个体智能:基于LLM的多智能体系统中的协作、故障归因与自我进化综述)[08:44] 🎥 Warp-as-History: Generalizable Camera-Controlled Video Generation from One Training Video(扭曲即历史:从单个训练视频实现可泛化的相机控制视频生成)[09:24] 🧠 PREPING: Building Agent Memory without Tasks(PREPING:无需任务构建智能体记忆)[10:04] 🧭 RouteProfile: Elucidating the Design Space of LLM Profiles for Routing(RouteProfile:阐明用于路由的LLM配置文件设计空间)[10:49] 🧠 EvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM Agents(EvolveMem:面向LLM智能体的自演化记忆架构通过自动研究实现)[11:28] 🧠 ATLAS: Agentic or Latent Visual Reasoning? One Word is Enough for Both(ATLAS:是智能体推理还是潜在视觉推理?一个词就足够了)【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

12分钟
99+
1个月前
2026.05.14 | MinT用LoRA补丁解决大模型规模难题;MulTaBench对齐图文任务小模型胜大模型

2026.05.14 | MinT用LoRA补丁解决大模型规模难题;MulTaBench对齐图文任务小模型胜大模型

HuggingFace 每日AI论文速递

【目录】本期的 15 篇论文如下:[00:25] 🏗 MinT: Managed Infrastructure for Training and Serving Millions of LLMs(MinT:用于训练和服务数百万大语言模型的托管基础设施)[01:08] 📊 MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image(MulTaBench:融合文本与图像的多模态表格学习基准测试)[02:14] 🎬 AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation(AnyFlow:任意步数视频扩散模型与在线流图蒸馏)[03:02] 📚 Training Long-Context Vision-Language Models Effectively with Generalization Beyond 128K Context(有效训练长上下文视觉语言模型,实现超越128K上下文的泛化能力)[03:48] 🤖 Predicting Decisions of AI Agents from Limited Interaction through Text-Tabular Modeling(从有限交互中通过文本-表格建模预测AI代理的决策)[04:27] 🖼 Qwen-Image-VAE-2.0 Technical Report(千问图像变分自编码器2.0技术报告)[05:05] 🎨 Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling(编辑指南针和编辑奖励指南针:图像编辑与奖励建模的统一基准)[06:01] 🎯 TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking(TrackCraft3R:将视频扩散变换器重新用于密集3D跟踪)[06:57] 🧠 Many-Shot CoT-ICL: Making In-Context Learning Truly Learn(多示例思维链上下文学习:让上下文学习真正学会)[07:58] 🎯 FrameSkip: Learning from Fewer but More Informative Frames in VLA Training(FrameSkip:在VLA训练中从更少但更具信息量的帧中学习)[08:52] 🌅 The DAWN of World-Action Interactive Models(世界-动作交互模型的黎明)[09:43] 🌊 Asymmetric Flow Models(非对称流模型)[10:24] 🤖 Learning Agentic Policy from Action Guidance(从行动引导中学习智能体策略)[11:23] 💻 Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation(检索成本低廉,给我看代码:面向检索增强生成的可执行多跳推理)[12:13] 🎬 PresentAgent-2: Towards Generalist Multimodal Presentation Agents(PresentAgent-2:迈向通用多模态演示智能体)【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

13分钟
99+
1个月前
2026.05.13 | 原生统一看画;边缘隐私记管

2026.05.13 | 原生统一看画;边缘隐私记管

HuggingFace 每日AI论文速递

【目录】本期的 15 篇论文如下:[00:23] 🧠 SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture(SenseNova-U1: 基于NEO-unify架构统一多模态理解与生成)[01:10] 🔒 MemPrivacy: Privacy-Preserving Personalized Memory Management for Edge-Cloud Agents(MemPrivacy:面向边缘-云智能体的隐私保护个性化记忆管理)[01:59] 🧠 $δ$-mem: Efficient Online Memory for Large Language Models(δ-mem:面向大型语言模型的高效在线记忆机制)[02:43] 🤖 RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards(RubricEM:超越可验证奖励的元强化学习与基于量规引导的策略分解)[03:33] 🤖 World Action Models: The Next Frontier in Embodied AI(世界动作模型:具身智能的下一个前沿)[04:22] 🤖 AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in UMMs via Decompositional Verifiable Reward(AlphaGRPO:通过分解可验证奖励解锁统一多模态模型中的自反思多模态生成)[05:09] 🧩 Beyond the Last Layer: Multi-Layer Representation Fusion for Visual Tokenization(超越最后一层:多层表示融合用于视觉标记化)[06:12] 🛠 ToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents(ToolCUA:面向计算机使用代理的最优GUI-工具路径编排)[06:51] 🏭 Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics(企业系统需要学习世界模型吗?上下文在推断动态中的重要性)[07:52] 🎨 L2P: Unlocking Latent Potential for Pixel Generation(L2P:解锁像素生成的潜在潜能)[08:33] 🎬 CausalCine: Real-Time Autoregressive Generation for Multi-Shot Video Narratives(CausalCine:面向多镜头视频叙事的实时自回归生成)[09:18] 🔍 Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents(面向视觉原生多模态深度搜索代理的在策略数据进化方法)[10:18] 💻 Teaching Language Models to Think in Code(教语言模型用代码思考)[10:58] 🛡 On-Policy Self-Evolution via Failure Trajectories for Agentic Safety Alignment(基于失败轨迹的在线策略自我进化方法用于智能体安全对齐)[11:52] 🌌 MCP-Cosmos: World Model-Augmented Agents for Complex Task Execution in MCP Environments(MCP-Cosmos:MCP环境中用于复杂任务执行的世界模型增强型智能体)【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

13分钟
85
1个月前
2026.05.12 | 数学家闭门出题考倒大模型;生图模型千字提示精准成画

2026.05.12 | 数学家闭门出题考倒大模型;生图模型千字提示精准成画

HuggingFace 每日AI论文速递

【目录】本期的 15 篇论文如下:[00:25] 🧮 Soohak: A Mathematician-Curated Benchmark for Evaluating Research-level Math Capabilities of LLMs(Soohak:由数学家策划的基准测试,用于评估大语言模型的研究级数学能力)[01:30] 🎨 Qwen-Image-2.0 Technical Report(Qwen-Image-2.0技术报告)[02:23] 🎥 CollabVR: Collaborative Video Reasoning with Vision-Language and Video Generation Models(CollabVR:基于视觉语言与视频生成模型的协作式视频推理)[03:08] 🧠 TMAS: Scaling Test-Time Compute via Multi-Agent Synergy(TMAS:通过多智能体协同扩展测试时计算)[03:52] 📄 PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documents(PaperFit:面向科学文档的视觉在环排版优化)[04:34] 📈 Model Merging Scaling Laws in Large Language Models(大语言模型中的模型合并缩放定律)[05:19] 🧩 Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training(几何冲突:解释并控制大语言模型持续后训练中的遗忘现象)[06:20] 🌍 WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors(世界推理基准:作为未来世界状态预测器的视频生成器的人类对齐压力测试)[07:12] 📊 Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria(自动评分标准作为奖励:从隐式偏好到显式多模态生成准则)[08:03] 🤖 X-OmniClaw Technical Report: A Unified Mobile Agent for Multimodal Understanding and Interaction(X-OmniClaw技术报告:一种用于多模态理解与交互的统一移动智能体)[08:51] 🧠 Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models(内存高效的循环Transformer:在循环语言模型中解耦计算与内存)[09:35] 🔄 SEIF: Self-Evolving Reinforcement Learning for Instruction Following(SEIF:面向指令跟随的自我进化强化学习)[10:19] 🔄 Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning(面向智能体强化学习的动态技能生命周期管理)[11:10] 🎨 Pixal3D: Pixel-Aligned 3D Generation from Images(Pixal3D: 从图像进行像素对齐的三维生成)[11:54] 🔄 Rebellious Student: Reversing Teacher Signals for Reasoning Exploration with Self-Distilled RLVR(叛逆学生:通过自蒸馏强化学习中的反向教师信号进行推理探索)【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

13分钟
66
1个月前
2026.05.11 | 音乐驱舞拆分专家;流匹配蒸馏全科状元

2026.05.11 | 音乐驱舞拆分专家;流匹配蒸馏全科状元

HuggingFace 每日AI论文速递

【目录】本期的 15 篇论文如下:[00:29] 💃 MACE-Dance: Motion-Appearance Cascaded Experts for Music-Driven Dance Video Generation(MACE-Dance:音乐驱动舞蹈视频生成的运动与外观级联专家模型)[01:07] 🎯 Flow-OPD: On-Policy Distillation for Flow Matching Models(Flow-OPD:面向流匹配模型的在线策略蒸馏)[01:58] 🎯 Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex(列表式策略优化:基于组的RLVR作为LLM响应单纯形上的目标投影)[02:52] 🔍 HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents(HyperEyes:面向并行多模态搜索代理的双粒度效率感知强化学习)[03:37] 🤖 LLMs Improving LLMs: Agentic Discovery for Test-Time Scaling(大语言模型自我进化:面向测试时扩展的智能体发现框架)[04:20] 🎥 HumanNet: Scaling Human-centric Video Learning to One Million Hours(HumanNet:将人类中心视频学习扩展到一百万小时)[05:09] 🧠 Mean Mode Screaming: Mean--Variance Split Residuals for 1000-Layer Diffusion Transformers(均值模式尖叫:面向千层扩散Transformer的均值-方差分裂残差)[06:06] 🔍 Beyond Retrieval: A Multitask Benchmark and Model for Code Search(超越检索:面向代码搜索的多任务基准与模型)[07:06] 🧩 Anisotropic Modality Align(各向异性模态对齐)[07:58] 🤖 AEM: Adaptive Entropy Modulation for Multi-Turn Agentic Reinforcement Learning(AEM:面向多轮智能体强化学习的自适应熵调制)[08:49] 📜 TextLDM: Language Modeling with Continuous Latent Diffusion(TextLDM:基于连续潜在扩散的语言建模)[09:41] 🧠 4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding(4D思考者:利用4D图像进行动态空间理解的思考)[10:25] 🎬 A$^2$RD: Agentic Autoregressive Diffusion for Long Video Consistency(A²RD:用于长视频一致性的智能自回归扩散模型)[11:04] 🛡 DecodingTrust-Agent Platform (DTap): A Controllable and Interactive Red-Teaming Platform for AI Agents(DecodingTrust-Agent平台(DTap):一个可控且可交互的AI智能体红队测试平台)[11:52] 🔍 MISA: Mixture of Indexer Sparse Attention for Long-Context LLM Inference(MISA:面向长上下文大语言模型推理的混合索引器稀疏注意力机制)【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

13分钟
75
1个月前

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