00:41:15 AI防忽悠指南：如何让聪明的机器不说胡话？ 

00:05:37 想变强？别再刷旧题了，你得学会自己“造”难题 

00:10:06 AI进阶的秘密：一行代码如何让“学霸”真正开窍？ 

00:14:46 AI的新玩法：从“搬运工”到“侦探” 

00:19:10 AI也会“想太多”？聊聊如何给模型一颗“定心丸” 

本期介绍的五篇论文：

[CL] Learning to Reason for Factuality  

[FAIR at Meta]  

https://arxiv.org/abs/2508.05618 

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[CL] MathSmith: Towards Extremely Hard Mathematical Reasoning by Forging Synthetic Problems with a Reinforced Policy  

[Tsinghua University]  

https://arxiv.org/abs/2508.05592 

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[LG] On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification  

[Southeast University & University of California, Los Angeles]  

https://arxiv.org/abs/2508.05629 

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[LG] GRAIL: Learning to Interact with Large Knowledge Graphs for Retrieval Augmented Reasoning  

[Tsinghua University]  

https://arxiv.org/abs/2508.05498 

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[CL] Efficient Reasoning for Large Reasoning Language Models via Certainty-Guided Reflection Suppression  

[Peking University & The Hong Kong University of Science and Technology]  

https://arxiv.org/abs/2508.05337