00:00:29 解锁AI推理能力：少即是多的秘密

00:05:17 AI巨兽的“成长配方”：如何让小个子智慧指导大块头？

00:10:03 AI作画的“临门一脚”：如何让快马跑得又快又好？

00:14:05 AI 创造 3D 模型：从“盖房子”到“捏泥人”

00:07:44 AI界的“小灶”，如何喂出绝顶高手？

本期介绍的五篇论文：

[LG] Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

[Alibaba Group]

https://arxiv.org/abs/2508.08221

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[LG] μ-Parametrization for Mixture of Experts

[University of Warsaw]

https://arxiv.org/abs/2508.09752

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[LG] Noise Hypernetworks: Amortizing Test-Time Compute in Diffusion Models

[Technical University of Munich & Inceptive]

https://arxiv.org/abs/2508.09968

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[CV] VertexRegen: Mesh Generation with Continuous Level of Detail

[Meta Reality Labs Research & UC San Diego]

https://arxiv.org/abs/2508.09062

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[LG] Beyond Scaling Law: A Data-Efficient Distillation Framework for Reasoning

[Zhongxing Telecom Equipment (ZTE)]

https://arxiv.org/abs/2508.09883

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[CL] Speed Always Wins: A Survey on Efficient Architectures for Large Language Models

[Unknown / Survey paper]

https://arxiv.org/abs/2508.09834

[人人能懂] AI的“小灶、泥人与神级助理”

AI可可AI生活