你有没有想过，AI也会有“选择困难症”吗？或者，怎么才能给AI请个既省钱又能干的“陪练”？这一期，我们就来聊聊几篇有趣的最新论文，看看科学家们是如何教会AI像高手一样反思、像侦探一样倾听“沉默的投票”，甚至用中学物理知识，给AI装上一双“3D眼睛”的。准备好了吗？让我们一起出发！00:00:29 鸡娃不如“陪练”，AI训练的降本增效新思路00:05:53 AI的学霸秘籍，如何像高手一样思考和进化00:12:12 AI的阅读术，如何既快又好地啃下海量信息？00:18:24 AI的“过分自信”，原来是种“选择困难症”00:23:39 让AI拥有“立体视觉”的省钱妙计本期介绍的几篇论文：[LG] CoDistill-GRPO: A Co-Distillation Recipe for Efficient Group Relative Policy Optimization [Google Research] https://arxiv.org/abs/2605.08873 ---[CL] RubricEM: Meta-RL with Rubric-guided Policy Decomposition beyond Verifiable Rewards [Google Cloud AI Research] https://arxiv.org/abs/2605.10899 ---[CL] Scratchpad Patching: Decoupling Compute from Patch Size in Byte-Level Language Models [Google DeepMind] https://arxiv.org/abs/2605.09630 ---[CL] The Silent Vote: Improving Zero-Shot LLM Reliability by Aggregating Semantic Neighborhoods [Google] https://arxiv.org/abs/2605.09739 ---[LG] RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings [Seoul National University & Google Research] https://arxiv.org/abs/2605.10706

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

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