[人人能懂AI前沿] AI的思考术：从逆向学习、技能博弈到情境安全

我们都希望AI能像人一样思考和成长，但你有没有想过，AI要如何向一位只做不说的“沉默高手”学到心法？又如何突破“刷题”瓶颈，进化到自己“编写教材”的境界？本期节目，我们将通过几篇最新论文，一起探寻AI如何拥有“复盘”的元认知能力，如何像人一样兼顾大局与细节，以及在复杂的指令面前，它究竟凭什么判断对错。准备好，我们马上进入AI的深度思考世界。

00:00:32 如何向一位沉默的高手学艺？

00:06:26 AI的自我进化，从“刷题”到“编教材”

00:11:54 同一个命令，AI凭什么判断对错？

00:18:33 AI的左右脑难题，如何让它既懂大局，又见细节？

00:25:12 如何让AI拥有“复盘”能力

本期介绍的几篇论文：

[LG] LeAct: Learning to Reason from Expert Actions

[Princeton University]

https://arxiv.org/abs/2607.21856

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[CL] Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills

[Qwen Large Model Application Team, Alibaba]

https://arxiv.org/abs/2607.22529

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[AI] Agent Security Needs Redefinition through a Holistic Framework

[UC Santa Cruz & UC Berkeley]

https://arxiv.org/abs/2607.22024

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[CV] Twins: Learn to Predict Unified Representations with Focal Loss

[The Chinese University of Hong Kong & Tencent, Hunyuan]

https://arxiv.org/abs/2607.22531

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[LG] Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning

[University of Illinois Urbana-Champaign]

https://arxiv.org/abs/2607.21971