AnalysisAI ModelsOctober 20, 2026

HarnessRL co-evolves training harness with policy for open-ended RL

Read original source →arxiv.org

HarnessRL pairs a policy with a co-evolving training harness that adapts task sampling, rollout guidance, and rubric updates to prevent reward failure in open-ended reinforcement learning. The paper targets non-discriminative and spurious rewards, using a just-in-time critic and a Rubric-Mix-10k dataset.

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