general family · filed under post-training
Reinforcement Learning Post-Training
Post-training with RL; the evidence does not identify a particular algorithm.
Also called RL post-training, larger-scale RL post-training.
- sources
- 2
- models
- 2
- lab adopt it
- 1
- strongest
- used
How sources treat it
One count per evidence span, weakest treatment to strongest.
mentioned 1used 1
Documented in
Evidence
2 spans quoted from the sources, strongest treatment first.
RL Post-training
usedpost trainingin Hy3Tencent Hunyuan
New pre-training methods + larger-scale RL post-training deliver benchmark results ahead of flagship models
mentionedpost trainingin DeepSeek-V4.1-FlashDeepSeek
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 LearningAbstention TrainingAdvantage ShapingAgentic RL Task MixCISPO with Length-Weighted Leave-One-Out Group-Relative AdvantagesConcatenated Routing ReplayDerived-Latency PenaltyDomain-Specialized RL ExpertsDomain-Specific GRPO TrainingDropping All-Zero-Advantage Groups