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101
发布:
3天前
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本期的 14 篇论文如下:
[00:17] 🏅 P1: Mastering Physics Olympiads with Reinforcement Learning(用强化学习攻克物理奥赛)
[00:56] 🌐 Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Data(Uni-MoE 2.0 Omni:以语言为中心的万模态大模型,通过先进MoE、训练与数据实现规模跃升)
[01:42] 🧩 Part-X-MLLM: Part-aware 3D Multimodal Large Language Model(Part-X-MLLM:面向部件感知的3D多模态大语言模型)
[02:22] 🧠 TiViBench: Benchmarking Think-in-Video Reasoning for Video Generative Models(TiViBench:视频生成模型思维推理基准测试)
[03:08] 🚀 GroupRank: A Groupwise Reranking Paradigm Driven by Reinforcement Learning(GroupRank:一种由强化学习驱动的分组重排范式)
[03:49] 🧩 PhysX-Anything: Simulation-Ready Physical 3D Assets from Single Image(PhysX-Anything:单张图像生成可仿真物理3D资产)
[04:28] 🌌 UFO$^3$: Weaving the Digital Agent Galaxy(UFO³:编织数字智能体银河)
[04:59] 🍲 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)
[05:38] 🌍 OlmoEarth: Stable Latent Image Modeling for Multimodal Earth Observation(OlmoEarth:面向多模态地球观测的稳定潜变量图像建模)
[06:19] 🔄 Live-SWE-agent: Can Software Engineering Agents Self-Evolve on the Fly?(Live-SWE-agent:软件工程智能体能否实时自我进化?)
[06:51] 🚀 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)
[07:36] 🎯 Test-Time Spectrum-Aware Latent Steering for Zero-Shot Generalization in Vision-Language Models(测试时谱感知潜变量引导实现视觉-语言模型零样本泛化)
[08:19] 🧠 WebCoach: Self-Evolving Web Agents with Cross-Session Memory Guidance(WebCoach:具备跨会话记忆引导的自进化网页智能体)
[09:10] 🧬 Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs(进化方法而非提示:面向大模型的越狱攻击演化合成)
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