Unverified50% confidenceFactExact time
Diffusion language models generate multiple tokens simultaneously through a parallel denoising process, promising to substantially reduce inference time.
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10/28/2026
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UnverifiedAfter removing the acoustic tokenizer, the model must model directly in a continuous acoustic space, typically relying on continuous generation paradigms such as diffusion models or flow matching, which shortens the inference pipeline.78% similarUnverified离散扩散语言模型主流方案包括：将token映射到连续嵌入空间进行扩散（如Diffusion-LM），或设计离散扩散过程用掩码模拟加噪（如D3PM、MDLM）72% similarUnverified流式推理技术让模型对持续到来的音频帧进行增量式处理，在达到足够置信度时立即开始输出，而非等待说话人完整停顿72% similarUnverifiedDiffusion language models still need to process all sequence positions at each denoising step, so parallel generation does not mean the end of computational waste.71% similar
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