This includes designing architectures that distill effectively, studying how teacher and student models should be trained together, and developing distillation methods that preserve reasoning, multimodal understanding, instruction following, and other important capabilities under constrained model capacity. Experience with knowledge distillation, including offline or off-policy distillation, on-policy distillation, self-distillation, sequence-level distillation, logic matching, or representation transfer.