2026.09.02 | 学生模拟器实现因材施教；自动驾驶模型融合感知规划。

【赞助商】OpenClaw快报每天五分钟，听听 OpenClaw 快报，带你了解最新动态和业内讨论传送门 https://www.xiaoyuzhoufm.com/podcast/6a1732a2dffa135d0ab5ef43【目录】本期的 15 篇论文如下：[00:28] 🎓 StudentSim: Training LLM-based Student Simulators（StudentSim：训练基于大语言模型的学生模拟器）[01:34] 🚗 Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving（Qwen-Drive-1.0：迈向自动驾驶视觉语言基础模型的第一步）[02:46] 🔁 SMELT: Scaling Laws for Compute-Matched MoE Looped Transformers（SMELT：计算匹配的MoE循环Transformer的缩放定律）[03:44] 🤖 UI-Venus-2 Technical Report（UI-Venus-2技术报告）[04:41] 🤖 ZimaBlue: Evolving Generalizable World Action Models through Scalable Video Pre-training（ZimaBlue：通过可扩展视频预训练演化可泛化的世界动作模型）[05:40] 🌍 H3-World: Turning Language Understanding into World Control（H3-World：将语言理解转化为世界控制）[06:41] 🔍 Hi-Q: Hierarchical Evidence-guided Query Refinement for Multi-Hop Question Answering（Hi-Q：层次化证据引导的多跳问答查询细化）[07:36] 🚁 Evaluating Multimodal LLMs as Generalist Vision-Language-Action Agents for Drone Control: Commanding, Approaching, Tracking and Searching（评估多模态大语言模型作为无人机控制的通用视觉-语言-行动智能体：指挥、接近、跟踪与搜索）[08:33] 🔗 Uncovering Understanding-Generation Synergy in Native Unified Multimodal Models: From Representation, Task to System（揭示原生统一多模态模型中理解与生成的协同效应：从表征、任务到系统）[09:27] 🛡 Safin-1: Safety from Within through Memory-Native State Evolution（Safin-1：通过记忆原生状态演化实现由内而外的安全）[10:24] 🏢 From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix（从生产流量到后训练：构建覆盖企业请求组合的自托管大语言模型）[11:15] 🩺 DiagEvo: Diagnosis-Guided Self-Evolution via Hierarchical Error Memory（DiagEvo：通过分层错误记忆进行诊断引导的自我进化）[12:07] 🧠 EM^2Mem: Event-Centric Multimodal Memory for Large Language Models（EM²Mem：面向大语言模型的事件中心多模态记忆）[13:09] 🤖 Harness-of-Harness: Multi-Day Autonomous Software Development with Continual Improvement（Harness-of-Harness：多日持续改进的自主软件开发）[14:07] 🛡 Control-Data Flow Separation: Stable Prompt Optimization in Multi-Agent LLMs（控制流与数据流分离：多智能体大语言模型中的稳定提示优化）【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