Under matched compute on Dream-7B and LLaDA-8B, ORM reranking beats deterministic PRM guidance by up to 82.71% versus 70.02%
The work introduces a forward-pass-matched diagnostic protocol for reward-guided reasoning in discrete diffusion language models and shows, on Dream-7B and LLaDA-8B-Base, that deterministic top-k process-reward-model guidance trails independent sampling plus task-matched outcome-reward-model reranking on GSM8K, MATH, and MBPP, decomposing the gap into candidate-pool damage from guidance and terminal selection quality.