Editorial context编辑说明
What this briefing adds本期解读价值
An interactive Echo workbench based on nrehiew's essay: compare SFT, RL, and OPD by target distribution, on-policy data, signal density, bias, forgetting, generalization, and the shape of a future post-training algorithm.
Echo adds source selection, synthesis, bilingual framing, and interaction design. This briefing is an independent editorial layer and does not replace the original work.
基于 nrehiew 文章制作的交互式分布工作台：用目标分布、on-policy 数据、信号密度、偏差、遗忘与泛化来比较 SFT、RL 和 OPD，并勾勒下一代后训练算法的形状。
Echo 在原始材料之上补充选题、信息综合、双语语境与交互设计。本页是独立编辑解读，不能替代原文。