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CREDO: Variance-Guided Rubric Evolution for Replay-Corrected Credit Assignment
Long-horizon language agents receive sparse terminal feedback, while intermediate rubrics provide structured but potentially misspecified assessments of progress. In resettable training environments, counterfactual continuation rollouts can measure local credit, but exhaustive replay is costly. We p
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