00:01:36 你的勤奋，是在“拼宽度”还是在“拼深度”？
00:06:00 AI 变聪明的秘密：不止是“喂饱”，更要“喂好”
00:11:19 AI的“学霸修炼手册”：如何跳出成长平台期？
00:16:15 给AI一个“提示”，解锁更高阶的智慧
00:20:23 你怎么用“临时工”大脑，摆平全世界？
00:05:30 喂AI，也是一门技术活
今天介绍的六篇论文：
[LG] The Serial Scaling Hypothesis
[UC Berkeley]
https://arxiv.org/abs/2507.125
---
[LG] Supervised Fine Tuning on Curated Data is Reinforcement Learning (and can be improved)
C Qin, J T Springenberg
https://arxiv.org/abs/2507.12856
---
[LG] Scaling Up RL: Unlocking Diverse Reasoning in LLMs via Prolonged Training
M Liu, S Diao, J Hu, X Lu...
[NVIDIA]
https://arxiv.org/abs/2507.12507
---
[CL] QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation
J Li, H Lu, K Wen, Z Yang...
[Ant Research & Shanghai Qi Zhi Institute & Stanford University & Tsinghua University]
https://arxiv.org/abs/2507.13266
---
[CL] Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models
L Wong, K M. Collins, L Ying, C E. Zhang...
[Stanford University & MIT]
https://arxiv.org/abs/2507.12547
---
[CL] A Survey of Context Engineering for Large Language Models
https://arxiv.org/abs/2507.13334