specific method · filed under post-training
Multi-Prefix Multi-Teacher On-Policy Distillation
Multi-teacher on-policy distillation combining autonomous student rollouts with prefix-conditioned single-turn rollouts.
- sources
- 3
- models
- 2
- lab adopt it
- 1
- strongest
- used
How sources treat it
One count per evidence span, weakest treatment to strongest.
used 3
Documented in
Evidence
3 spans quoted from the sources, strongest treatment first.
After mixed RL, MOPD2 combines autonomous student rollouts with prefix-conditioned single-turn rollouts (Teacher-Prefix and SFT-Prefix)
usedpost trainingin MiMo-V2.6-Pro-RLXiaomi
After mixed RL, we use Multi-Prefix Multi-Teacher On-Policy Distillation (MOPD2) to combine capabilities from teachers trained for different tasks
usedunclearin MiMo-V2.6Xiaomi
MOPD2 combines autonomous student rollouts with prefix-conditioned single-turn rollouts (Teacher-Prefix and SFT-Prefix)
usedpost trainingin MiMo-V2.6-Flash-RLXiaomi
Filed alongside
Other methods under post-training :: policy distillation.
Multi-Teacher On-Policy DistillationOn-Policy DistillationPrefix-Conditioned On-Policy DistillationSpecialist DistillationAutonomous Student RolloutsLarge-Scale On-Policy DistillationOn-Policy Cross-Stage DistillationAsynchronous Multi-Teacher On-Policy DistillationBehavior–Proximal Policy DecouplingDistillation Fine-Tuning on MiMo-Generated DataDistillation for Post-Training Data GenerationIcePop Token-Level Loss MaskingModel DistillationMulti-Objective Policy DistillationOff-Policy DistillationPer-Token On-Policy Distillation RewardSFT–RL–On-Policy Distillation PipelineTeacher-Trajectory and SFT-History Reuse