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通勤路上就听AI每周谈。AI每周谈,每周带你回顾上周AI大事
传送门 🔗https://www.xiaoyuzhoufm.com/podcast/688a34636f5a275f1cba40fd
【目录】
本期的 15 篇论文如下:
[00:32] 👁 CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding(CodeOCR:视觉语言模型在代码理解中的有效性研究)
[01:18] 🤖 AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration(AOrchestra:面向智能体编排的子智能体自动创建)
[02:01] 🔍 No Global Plan in Chain-of-Thought: Uncover the Latent Planning Horizon of LLMs(思维链中无全局规划:揭示大语言模型的潜在规划视野)
[02:43] 🔗 daVinci-Agency: Unlocking Long-Horizon Agency Data-Efficiently(daVinci-Agency:高效解锁长程智能体工作流)
[03:23] 🧠 Research on World Models Is Not Merely Injecting World Knowledge into Specific Tasks(世界模型研究并非仅将世界知识注入特定任务)
[04:06] 🎬 3D-Aware Implicit Motion Control for View-Adaptive Human Video Generation(面向视角自适应人体视频生成的3D感知隐式运动控制)
[04:56] 🤖 MARS: Modular Agent with Reflective Search for Automated AI Research(MARS:具备反思搜索能力的模块化智能体用于自动化人工智能研究)
[05:41] 📊 CoBA-RL: Capability-Oriented Budget Allocation for Reinforcement Learning in LLMs(CoBA-RL:面向大语言模型强化学习的基于能力的预算分配算法)
[06:25] ⚡ Diversity-Preserved Distribution Matching Distillation for Fast Visual Synthesis(保持多样性的分布匹配蒸馏用于快速视觉合成)
[07:19] 🤖 SWE-World: Building Software Engineering Agents in Docker-Free Environments(SWE-World:在无Docker环境中构建软件工程智能体)
[08:09] 🤖 SWE-Master: Unleashing the Potential of Software Engineering Agents via Post-Training(SWE-Master:通过后训练释放软件工程智能体的潜力)
[09:14] 📊 Learning Query-Specific Rubrics from Human Preferences for DeepResearch Report Generation(基于人类偏好的查询特定评分规则学习用于深度研究报告生成)
[10:08] ⚡ Parallel-Probe: Towards Efficient Parallel Thinking via 2D Probing(Parallel-Probe:通过二维探测实现高效并行思维)
[10:59] 🎯 Unified Personalized Reward Model for Vision Generation(视觉生成的统一个性化奖励模型)
[11:47] 🔍 WideSeek: Advancing Wide Research via Multi-Agent Scaling(WideSeek:通过多智能体扩展推进广度研究)

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