无需训练的dLLMs推理加速方法，用草稿引导连续跳跃解码，提升效率且保持质量
arXiv:2607.20467v1 Announce Type: new Abstract: While parallel decoding is central to the efficiency of Diffusion Large Language Models (dLLMs), curre…
DLLM解码计算并行化存在严重低效，只有少数token可解码，此文精准定位瓶颈并提出优化方向。
arXiv:2601.23278v2 Announce Type: replace Abstract: Diffusion Large Language Models (DLLMs) offer a compelling alternative to Auto-Regressive models, …
新型扩散语言模型并行解码方法DMax，通过自精炼机制减少误差累积，实现高并行度高质量生成。
arXiv:2604.08302v3 Announce Type: replace-cross Abstract: We present DMax, a new paradigm for efficient diffusion language models (dLLMs). It mitigate…