implementation detail · filed under post-training
Group-Relative Advantage Normalization Within Effort-Level Subgroups
Mean-centering rewards to compute group-relative advantages among responses sharing the same prompt and effort level.
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Responses sharing the same (𝑥,𝑏) form a subgroup, within which rewards are mean-centered to compute group-relative advantages.
usedtraining objectivein DeepSeek-V4.1DeepSeek
Filed alongside
Other methods under post-training :: reinforcement learning algorithm.
Group Relative Policy OptimizationReinforcement LearningGroupwise Advantage RedistributionFreezing the MoE Router During Reinforcement LearningIcePopOff-Policy Sequence MaskingReinforcement Learning from Verifiable RewardsRollout Routing ReplayUnbiased KL EstimateAsynchronous Group Relative Policy OptimizationChain-of-Thought Reinforcement LearningDirect Double-Sided Importance SamplingKeep Sampling MaskMixed Reinforcement LearningPivot Reinforcement LearningReinforcement Learning Post-TrainingAbstention TrainingAdvantage ShapingAgentic RL Task MixCISPO with Length-Weighted Leave-One-Out Group-Relative AdvantagesConcatenated Routing ReplayDerived-Latency PenaltyDomain-Specialized RL ExpertsDomain-Specific GRPO Training