当AI看似无所不知时，它真的理解自己说的因果关系吗？我们如何训练AI学会“解释自己”而不是“强词夺理”？本期节目，我们将从几篇最新论文出发，揭示AI如何学会编织知识地图、为何会“一本正经地胡说八道”，并一窥它那“不断复读”的内在工作模式，以及为电影特效“脑补”真实细节的惊人能力。

00:00:29 AI时代的“寻龙诀”，我们如何挖掘知识的因果龙脉

00:07:37 AI正在给你一种“知道”的幻觉

00:14:50 AI看病，如何才能“说人话”还“负责任”？

00:19:48 AI的“偷懒”智慧，为什么顶尖模型都在悄悄“复读”？

00:25:42 AI正在“脑补”你看不到的真实

本期介绍的几篇论文：

[LG] Large Causal Models from Large Language Models

[Adobe Research]

https://arxiv.org/abs/2512.07796

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[AI] Epistemological Fault Lines Between Human and Artificial Intelligence

[Sapienza University of Rome & University of Milan Bicocca & University of Maribor]

https://arxiv.org/abs/2512.19466

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[LG] Reason2Decide: Rationale-Driven Multi-Task Learning

[University of Alberta]

https://arxiv.org/abs/2512.20074

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[CV] Block-Recurrent Dynamics in Vision Transformers

[Harvard University]

https://arxiv.org/abs/2512.19941

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[CV] Over++: Generative Video Compositing for Layer Interaction Effects

[University of North Carolina at Chapel Hill & University of Maryland]

https://arxiv.org/abs/2512.19661