---
id: 20260604-T0-08
title: "Fast-dLLM++加速扩散模型推理"
title_en: "Fast-dLLM++ Accelerates Diffusion Model Inference"
url: https://ai.daily.yangsir.net/daily/20260604-T0-08
issue_date: 2026-06-04
publish_date: 2026-06-03T04:00:00.000Z
category: research
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2606.02955
---

# Fast-dLLM++加速扩散模型推理

研究人员提出Fast-dLLM++技术，通过Fréchet Profile解码方法显著提升扩散大语言模型推理速度。该方法优化了掩码令牌的安全决策机制，支持更高效的并行生成。实验显示，在保持生成质量的同时，推理速度提升2-3倍，特别适合需要快速响应的文本生成应用。

## English Version

**Fast-dLLM++ Accelerates Diffusion Model Inference**

Researchers propose Fast-dLLM++ with Fréchet Profile decoding to significantly accelerate diffusion LLM inference. The method optimizes safe token decision-making for more efficient parallel generation. Experiments show 2-3x speedup with maintained quality, ideal for fast-response text generation applications.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2606.02955)

**详情页**：https://ai.daily.yangsir.net/daily/20260604-T0-08

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