implementation detail · filed under post-training
IcePop Token-Level Loss Masking
A token-level loss-masking strategy identified as IcePop.
Also called token-level masking using IcePop strategy.
- source
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- model
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- lab adopt it
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How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
m_t represents token-level masking using IcePop strategy
usedunclearin Nemotron 3 UltraNVIDIA
Filed alongside
Other methods under post-training :: policy distillation.
Multi-Teacher On-Policy DistillationOn-Policy DistillationPrefix-Conditioned On-Policy DistillationMulti-Prefix Multi-Teacher 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 GenerationModel DistillationMulti-Objective Policy DistillationOff-Policy DistillationPer-Token On-Policy Distillation RewardSFT–RL–On-Policy Distillation PipelineTeacher-Trajectory and SFT-History Reuse