Exploring More, Reasoning Better: Stepwise Risk-Sensitive GRPO for Diffusion Language Models
Diffusion large language models (dLLMs) generate text by denoising a sequence or successive blocks, allowing several tokens to be revealed in parallel. Reinforcement learning with verifiable rewards (RLVR) reuses terminal feedback across these decisions, even as their conditioning context changes. We propose stepwise r...
Yu Yue, Bo-Wen Zuo, David J. Crandall et al.
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