EAPO: entropy-guided credit assignment for RLVR improves exploration in LLM reasoning
coallaoh · x · 2026-09-29
A new method, EAPO (Entropic Advantage Policy Optimization), tackles the problem that success under uncertainty is hard to repeat while confident failures recur, using entropy-guided credit assignment for RLVR that treats success and failure asymmetrically:
- Reinforce surprising success at high-entropy decisions
- Penalize repeated failure more strongly at low-entropy decisions
- Soften penalties at uncertain decisions to preserve alternatives for recovery
Without auxiliary models, token-level supervision, or substantial extra computation, EAPO achieves the best overall results across base and reasoning backbones on diverse reasoning benchmarks.
Related event: EAPO: Entropy-Guided Credit Assignment for LLM Reasoning RL(2 posts)→
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