AI
Waypoint-OPD: teaching small models only what a big model learned consistently
Bingxi Hou, Guochao Jiang, Guofeng Quan, et al. · Submitted 15 Oct 2026 · 668 upvotes yesterday
Preprint · not peer reviewedTrending
When a teacher model is improved by trial-and-error training, its lessons can be passed to a student model. This method checks a mid-training snapshot of the teacher and only passes on changes that pointed the same way early and late.
Key finding: Across six maths and code settings with three student sizes, it scored best among the distillation methods compared, for one extra scoring pass.
Why it matters: It is a cheap way to make smaller models pick up the reliable parts of a bigger model's training.