They should use this idea to do weight-space distillation, feels like you can get far with small model by just collecting paired examples, discovering behavioral directions and using linear programming to find sparse weight edits to improve target behavior / limit unwanted changes, rinse repeat.

While we're at it, this whole reasoning tokens RL/distillation should be encouraging hierarchical reasoning – start with establishing high level abstractions first, then progressively refining it into lower level details – imho it would help with reasoning itself and would make it way easier to score/distill later as well.