outcome-rewards

This paper systematically compares process and outcome reward structures for reinforcement learning with verifiable rewards (RLVR) in small language models for mathematical reasoning. The study finds that process-only supervision significantly improves accuracy and reasoning trace fidelity over outcome-only supervision, and analyzes failure modes.