【月末特辑】11月最火AI论文 | Kandinsky 5.0全家桶开源;视频生成让模型边播边想
Description
本期的 10 篇论文如下:
[00:35 ] TOP1(🔥219) | 🎨 Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation(Kandinsky 5.0:用于图像和视频生成的基础模型家族)
[02:45 ] TOP2(🔥207) | 🎬 Thinking with Video: Video Generation as a Promising Multimodal Reasoning Paradigm(用视频思考:视频生成作为统一多模态推理新范式)
[04:58 ] TOP3(🔥191) | 🌍 Lumine: An Open Recipe for Building Generalist Agents in 3D Open Worlds(Lumine:在3D开放世界中打造通才智能体的开源方案)
[07:26 ] TOP4(🔥166) | ⚡ ROOT: Robust Orthogonalized Optimizer for Neural Network Training(ROOT:面向神经网络训练的鲁棒正交化优化器)
[09:37 ] TOP5(🔥156) | 🚀 MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling(MiroThinker:通过模型、上下文与交互扩展,将开源研究智能体性能推向新边界)
[11:54 ] TOP6(🔥151) | 🧠 General Agentic Memory Via Deep Research(通过深度研究的通用代理记忆)
[13:55 ] TOP7(🔥131) | 🏅 P1: Mastering Physics Olympiads with Reinforcement Learning(用强化学习攻克物理奥赛)
[16:01 ] TOP8(🔥131) | 🍲 Souper-Model: How Simple Arithmetic Unlocks State-of-the-Art LLM Performance(“汤”级模型:简单加权平均即可让大语言模型性能跃升)
[18:03 ] TOP9(🔥126) | 🧠 Tiny Model, Big Logic: Diversity-Driven Optimization Elicits Large-Model Reasoning Ability in VibeThinker-1.5B(小模型大逻辑:多样性驱动优化唤醒VibeThinker-1.5B的大模型推理力)
[20:14 ] TOP10(🔥121) | 🚀 Diffusion Language Models are Super Data Learners(扩散语言模型是超级数据学习者)
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