DGPO is a critic-free RL framework that uses bounded Hellinger distance and entropy-gated advantage redistribution to enable fine-grained token-level credit assignment in long CoT generations for LLM alignment, reporting SOTA results on AIME benchmarks.
Groundedprm: Tree-guided and fidelity-aware process reward modeling for step-level reasoning
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RREDCoT approximates segment-level reward redistribution for CoT traces by querying the model itself, offering a lower-cost alternative to Monte Carlo credit assignment in reasoning-model RL.
citing papers explorer
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DGPO: Distribution Guided Policy Optimization for Fine Grained Credit Assignment
DGPO is a critic-free RL framework that uses bounded Hellinger distance and entropy-gated advantage redistribution to enable fine-grained token-level credit assignment in long CoT generations for LLM alignment, reporting SOTA results on AIME benchmarks.
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RREDCoT: Segment-Level Reward Redistribution for Reasoning Models
RREDCoT approximates segment-level reward redistribution for CoT traces by querying the model itself, offering a lower-cost alternative to Monte Carlo credit assignment in reasoning-model RL.