你有没有想过，最聪明的决策，也许是先用最小的力气排除所有错误选项？当AI变得越来越话痨时，我们该如何给它请一位“效率教练”？为了把强大的AI装进你的手机，科学家又想出了怎样统一又精简的“节食计划”？本期节目，我们将通过几篇最新论文，一起探讨AI如何学会“先探路再铺路”的决策智慧，如何治好自己的“路痴”毛病，甚至如何掌握“动态开关”这门最高级的偷懒艺术。00:00:33 聪明人的偷懒指南，如何用最少的力气，走最对的路？00:07:16 AI话痨怎么办？聪明还得会省钱00:12:27 AI的“节食计划”，如何在你的手机里装下一个图书馆？00:17:42 大模型越来越聪明，为什么还是个“路痴”？00:22:45 为什么说，最高级的AI，必须学会“偷懒”？本期介绍的几篇论文：[CL] Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning [INRIA Lille & Google DeepMind] https://arxiv.org/abs/2604.14974 ---[CL] CROP: Token-Efficient Reasoning in Large Language Models via Regularized Prompt Optimization [Google LLC & Purdue University] https://arxiv.org/abs/2604.14214 ---[IR] A Unified Model and Document Representation for On-Device Retrieval-Augmented Generation [University of Massachusetts Amherst & Google] https://arxiv.org/abs/2604.14403 ---[CL] Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation [Georgia Institute of Technology & Microsoft] https://arxiv.org/abs/2604.14339 ---[CL] Compressed-Sensing-Guided, Inference-Aware Structured Reduction for Large Language Models [UC Berkeley] https://arxiv.org/abs/2604.14156

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

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