CreditDecoding: Accelerating Parallel Decoding in Diffusion Large Language Models with Trace Credits

Diffusion large language models (dLLMs) generate text through iterative denoising steps, achieving parallel decoding by denoising only high-confidence positions at each step. However, existing approaches often repetitively remask tokens due to initially low confidence scores, leading to redundant it... View More