今天，我们一同窥见了AI世界精巧的另一面：从注意力机制中类似“机械”的斜杠模式，到并行专家协作的优雅高效；从学会“如何选择”的元认知智慧，到预判趋势实现加速的数学之美，再到机器人通过巧妙设计获得的“分寸感”。这些最新论文告诉我们，通往更强人工智能的道路，不仅需要强大的算力，更充满了令人惊叹的巧思与智慧。00:00:29 大模型里的‘斜杠’，一个被忽视的注意力模式00:08:32 AI变聪明的秘密，不是读得更多，而是问得更巧00:14:06 炼成全能AI的关键一步，选对方法，比埋头苦干更重要00:20:15 AI绘画加速的秘密，如何让机器“预见”未来？00:25:36 机器人干活儿，差的那点“分寸感”怎么补？本期介绍的几篇论文：[LG] Demystifying the Slash Pattern in Attention: The Role of RoPE[National University of Singapore]https://arxiv.org/abs/2601.08297---[CL] Parallel Context-of-Experts Decoding for Retrieval Augmented Generation[EURECOM]https://arxiv.org/abs/2601.08670---[LG] SimMerge: Learning to Select Merge Operators from Similarity Signals[Cohere & Google]https://arxiv.org/abs/2601.09473---[LG] High-accuracy and dimension-free sampling with diffusions[UC Berkeley & Harvard University]https://arxiv.org/abs/2601.10708---[RO] In-the-Wild Compliant Manipulation with UMI-FT[Stanford University]https://arxiv.org/abs/2601.09988

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

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