arXiv Machine Learning
Temporal Self-Distillation: Faster Inference in Discrete Diffusion Language Models
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FlowBlock: Wavefront-Parallel Decoding for Self-Correcting Diffusion Language Models
Block-wise diffusion large language models (dLLMs) decode sequentially at the block level, enabling effective KV-cache reuse across blocks but making inter-block decoding strictly serial. Prior work has attempted to unlock inter-block parallelism through post-training methods, but achieves only modest speedups and often degrades accuracy.