[人人能懂] 如何“教”AI忘记？——智能模型的“断舍离”艺术

00:00:32 你的夸奖，正在“毒害”AI 00:05:22 数据大扫除：不止是扔垃圾，更是换风格00:10:55 AI的“世界观”：它如何从零开始看懂现实？ 00:15:46 AI的“省钱攻略”：如何花小钱办大事？ 00:20:27 喂养AI的新艺术：从“吃什么”到“怎么吃” 本期介绍的无篇文章：[LG] Off-Policy Corrected Reward Modeling for Reinforcement Learning from Human Feedback  [The University of Tokyo and RIKEN AIP]  https://arxiv.org/abs/2507.15507  ---[LG] Distributional Unlearning: Forgetting Distributions, Not Just Samples  [EPFL & Stanford University]  https://arxiv.org/abs/2507.15112  ---[LG] Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning  [Max Planck Institute for Intelligent Systems & University of Tübingen]  https://arxiv.org/abs/2507.14748  ---[CL] Towards Compute-Optimal Many-Shot In-Context Learning  [Google Cloud AI Research]  https://arxiv.org/abs/2507.16217  ---[LG] LLM Data Selection and Utilization via Dynamic Bi-level Optimization  [University of Chinese Academy of Sciences & Huawei Noah’s Ark Lab]  https://arxiv.org/abs/2507.16178  在小宇宙查看该单集文稿