00:00:28 AI的“学霸”和“教练”，如何合二为一？00:04:33 想让AI更聪明？关键不是砸钱，是“会花钱”00:08:26 AI的“朋友圈”：单个脑补，不如组团思考00:13:12 如何让AI既是“通才”，又是“专才”？00:16:07 数据世界的“蝴蝶效应”：我们如何揪出那个扇动翅膀的“坏数据”？本期介绍的五篇论文：[LG] Your Reward Function for RL is Your Best PRM for Search: Unifying RL and Search-Based TTS [Rutgers University & Nanyang Technological University] https://arxiv.org/abs/2508.14313 ---[LG] Compute-Optimal Scaling for Value-Based Deep RL [UC Berkeley] https://arxiv.org/abs/2508.14881 ---[LG] Graph Concept Bottleneck Models [Stony Brook University & University of California, San Diego & IBM Research] https://arxiv.org/abs/2508.14255 ---[LG] Amortized Bayesian Meta-Learning for Low-Rank Adaptation of Large Language Models [Princeton University] https://arxiv.org/abs/2508.14285 ---[LG] Understanding Data Influence with Differential Approximation [University of Hong Kong & Chinese University of Hong Kong] https://arxiv.org/abs/2508.14648

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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