大大方方地做自己吧，带着你所有的“不完美”和“异常值”。

00:00:34 AI侦探养成记：如何让机器学会“死磕到底”？ 00:04:22 AI也需要“元学习”：如何打造一把能开万能锁的钥匙？ 00:07:56 拆解AI大脑：它如何学会“绕个弯”解决问题？ 00:12:21 AI学会“举一反三”的秘密：两层楼就够了？ 00:16:34 AI思考的秘密：为什么“少”就是“多”？ 本期介绍的五篇论文： [CL] Beyond Ten Turns: Unlocking Long-Horizon Agentic Search with Large-Scale Asynchronous RL [Tsinghua University] https://arxiv.org/abs/2508.079 --- [LG] AdaptFlow: Adaptive Workflow Optimization via Meta-Learning [Peking University & University of Chinese Academy of Sciences] https://arxiv.org/abs/2508.08053 --- [LG] Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent [CMU & UPenn & OSU] https://arxiv.org/abs/2508.08222 --- [LG] What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains [MIT & EPFL & UC Berkeley] https://arxiv.org/abs/2508.07208 --- [CL] Less Is More: Training-Free Sparse Attention with Global Locality for Efficient Reasoning [Princeton University & CMU] https://arxiv.org/abs/2508.07101

那个能一键“扭转乾坤”的开发者，不是别人，就是你自己。

00:00:30 AI界的“学霸”是怎么炼成的？ 00:04:45 你的下一个AI，为什么必须是个“行动派”？ 00:08:35 AI当上帝：从零开始创造一门语言 00:13:09 如何给AI大模型“摸骨”，看透它的知识边界？ 本期介绍的四篇论文： [CL] UR²: Unify RAG and Reasoning through Reinforcement Learning [Tsinghua University & Hebei University of Economics and Business] https://arxiv.org/abs/2508.06165 --- [CL] GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models [Zhipu AI & Tsinghua University] https://arxiv.org/abs/2508.06471 --- [CL] ConlangCrafter: Constructing Languages with a Multi-Hop LLM Pipeline [Tel Aviv University & UC Berkeley] https://arxiv.org/abs/2508.06094 --- [CL] Efficient Knowledge Probing of Large Language Models by Adapting Pre-trained Embeddings [Georgia Institute of Technology & MIT] https://arxiv.org/abs/2508.06030