
11 月 10 日 · 26 分钟
![[人人能懂] 从死记硬背到举一反三的五堂课](https://media-one.wavpub.com/covers/1b225f87-4eea-40e2-9522-fb4563ec9b2c/d48cb32e6dd1d52c.png?x-oss-process=image/resize,m_lfit,w_520,h_520/format,webp)
高手过招:抄作业还是自己闯?
AI也会“喜新厌旧”?高手是如何做到“学而不忘”的
让AI学会“脑补”,速度提升5倍的秘密
AI的“开窍”秘诀:如何让机器学会举一反三?
聪明反被聪明误?AI的“笨办法”
本期介绍的五篇论文:
[LG] Towards a Unified View of Large Language Model Post-Training
[Tsinghua University]
https://arxiv.org/abs/2509.04419
---
[LG] RL's Razor: Why Online Reinforcement Learning Forgets Less
[MIT]
https://arxiv.org/abs/2509.04259
---
[LG] Set Block Decoding is a Language Model Inference Accelerator
[FAIR at Meta]
https://arxiv.org/abs/2509.04185
---
[LG] ArcMemo: Abstract Reasoning Composition with Lifelong LLM Memory
[University of California, San Diego]
https://arxiv.org/abs/2509.04439
---
[LG] Learning When to Plan: Efficiently Allocating Test-Time Compute for LLM Agents
[University College London & University of Oxford]
https://arxiv.org/abs/2509.03581
说明里标出的时间点,点一下跳过去

11 月 10 日 · 26 分钟

[人人能懂AI前沿] 3D持续打磨、多智能体博弈与微米级控制
11 月 9 日 · 24 分钟

[人人能懂AI前沿] 从元技能提炼、对抗性推理到物理世界的“柔性破界”
11 月 8 日 · 23 分钟

[人人能懂AI前沿] 从分配脑容量、无反馈破局到预测未来的代价
11 月 7 日 · 24 分钟
![[人人能懂] 从死记硬背到举一反三的五堂课](https://media-one.wavpub.com/covers/1b225f87-4eea-40e2-9522-fb4563ec9b2c/d48cb32e6dd1d52c.png?x-oss-process=image/resize,m_lfit,w_400,h_400/format,webp)
AI可可AI生活 · 2025 年 9 月 6 日 · 23 分钟
高手过招:抄作业还是自己闯?
AI也会“喜新厌旧”?高手是如何做到“学而不忘”的
让AI学会“脑补”,速度提升5倍的秘密
AI的“开窍”秘诀:如何让机器学会举一反三?
聪明反被聪明误?AI的“笨办法”
本期介绍的五篇论文:
[LG] Towards a Unified View of Large Language Model Post-Training
[Tsinghua University]
https://arxiv.org/abs/2509.04419
---
[LG] RL's Razor: Why Online Reinforcement Learning Forgets Less
[MIT]
https://arxiv.org/abs/2509.04259
---
[LG] Set Block Decoding is a Language Model Inference Accelerator
[FAIR at Meta]
https://arxiv.org/abs/2509.04185
---
[LG] ArcMemo: Abstract Reasoning Composition with Lifelong LLM Memory
[University of California, San Diego]
https://arxiv.org/abs/2509.04439
---
[LG] Learning When to Plan: Efficiently Allocating Test-Time Compute for LLM Agents
[University College London & University of Oxford]
https://arxiv.org/abs/2509.03581
说明里标出的时间点,点一下跳过去

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11 月 10 日 · 26 分钟

[人人能懂AI前沿] 3D持续打磨、多智能体博弈与微米级控制
11 月 9 日 · 24 分钟

[人人能懂AI前沿] 从元技能提炼、对抗性推理到物理世界的“柔性破界”
11 月 8 日 · 23 分钟