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本期的 9 篇论文如下:
[00:26] 🧠 3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding(3DGraphLLM:结合语义图与大型语言模型进行三维场景理解)
[01:11] 🖼 DepthLab: From Partial to Complete(DepthLab:从部分到完整)
[01:54] 📊 Fourier Position Embedding: Enhancing Attention's Periodic Extension for Length Generalization(傅里叶位置嵌入:增强注意力机制的周期性扩展以实现长度泛化)
[02:35] 🎥 DiTCtrl: Exploring Attention Control in Multi-Modal Diffusion Transformer for Tuning-Free Multi-Prompt Longer Video Generation(DiTCtrl:探索多模态扩散变压器中的注意力控制以实现无需调优的多提示长视频生成)
[03:26] 🤔 In Case You Missed It: ARC 'Challenge' Is Not That Challenging(你可能错过了:ARC '挑战' 并不那么具有挑战性)
[04:02] 🧠 ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing(ReMoE:使用ReLU路由的全可微分专家混合模型)
[04:41] 🧩 PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models(PartGen:基于多视角扩散模型的部分级三维生成与重建)
[05:20] 🧠 SKETCH: Structured Knowledge Enhanced Text Comprehension for Holistic Retrieval(SKETCH:结构化知识增强的文本理解与整体检索)
[06:02] 🧠 Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning(通过过程奖励引导的树搜索集成大语言模型以提升复杂推理能力)
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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
本期的 9 篇论文如下:
[00:26] 🧠 3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding(3DGraphLLM:结合语义图与大型语言模型进行三维场景理解)
[01:11] 🖼 DepthLab: From Partial to Complete(DepthLab:从部分到完整)
[01:54] 📊 Fourier Position Embedding: Enhancing Attention's Periodic Extension for Length Generalization(傅里叶位置嵌入:增强注意力机制的周期性扩展以实现长度泛化)
[02:35] 🎥 DiTCtrl: Exploring Attention Control in Multi-Modal Diffusion Transformer for Tuning-Free Multi-Prompt Longer Video Generation(DiTCtrl:探索多模态扩散变压器中的注意力控制以实现无需调优的多提示长视频生成)
[03:26] 🤔 In Case You Missed It: ARC 'Challenge' Is Not That Challenging(你可能错过了:ARC '挑战' 并不那么具有挑战性)
[04:02] 🧠 ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routing(ReMoE:使用ReLU路由的全可微分专家混合模型)
[04:41] 🧩 PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models(PartGen:基于多视角扩散模型的部分级三维生成与重建)
[05:20] 🧠 SKETCH: Structured Knowledge Enhanced Text Comprehension for Holistic Retrieval(SKETCH:结构化知识增强的文本理解与整体检索)
[06:02] 🧠 Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning(通过过程奖励引导的树搜索集成大语言模型以提升复杂推理能力)
【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