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FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience

Huang, Zixun et al.
arXiv (All) · Papers
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artificial-intelligencemachine-learning
A reasoning model can improve from its own on-policy experience, but this inner loop is fragile: terminal verifiers provide reliable yet sparse supervision, while dense same-model guidance can reinforce false confidence or overconcentrate learning on a narrow solution mode. We introduce FlowBalance,
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