Jie Xiao

Back on Track: Aligning Rewards and States for Reasoning in Diffusion Large Language Models

This work introduces Process Aligned Policy Optimization (PAPO), a novel framework that holistically aligns the RL update with the dLLM's generative trajectory via Step-Aware Process Rewards (SPR) that transform sparse terminal rewards into dense, step-wise credit, and Entropy-Guided Historical Re-enactment that replay...