implementation detail · filed under post-training
Per-Token Tool-Error Step Penalty
Applying a small negative reward to the tokens of an assistant step whose tool invocation caused an execution error.
Also called Tool-error step penalty.
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Evidence
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for every assistant step whose tool invocation led to the error in tool execution, we apply a small negative reward to exactly the tokens that constituted that step, rather than to the trajectory as a whole.
usedtraining objectivein LAGUNA M.1/XS.2Poolside
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