从“战略指纹”到“解耦赋分”：AI的非技术性进化

00:01:29 AI的“人设”：谷歌“腹黑”，OpenAI“傻白甜”？ 00:06:09 给AI“减肥餐”：为什么数据越多，模型可能越笨？ 00:10:32 AI训练场上的新策略：先当“神算子”，再做“阅读家”00:14:53 功劳簿到底该怎么写？ 今天介绍的四篇论文：[LG] Strategic Intelligence in Large Language Models: Evidence from evolutionary Game TheoryK Payne, B Alloui-Cros  [King’s College London & University of Oxford]  https://arxiv.org/abs/2507.02618---[LG] Data Uniformity Improves Training Efficiency and More, with a Convergence Framework Beyond the NTK RegimeY Wang, S Gu  [Johns Hopkins University & UC Berkeley]  https://arxiv.org/abs/2506.24120---[CL] Should We Still Pretrain Encoders with Masked Language Modeling?H Gisserot-Boukhlef, N Boizard, M Faysse, D M. Alves...  [Artefact Research Center & Diabolocom & Illuin Technology]  https://arxiv.org/abs/2507.00994---[LG] Disentangled Feature ImportanceJ Du, K Roeder, L Wasserman  [CMU]  https://arxiv.org/abs/2507.00260在小宇宙查看该单集文稿