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English(EN) LiLiCorr: Lightweight Likelihood Correlation of Parallel Drafts for Speculative Decoding

新研究探索用于大型语言模型推测性解码的并行草稿

作者 PulseAugur 编辑部 · [2 个来源] ·

两篇新研究论文探讨了大型语言模型推测性解码的进展，重点关注提高并行草稿的效率和连贯性。第一篇论文调查了块并行推测性解码在多模态模型中的适用性，分析了各种架构和基准。第二篇论文介绍了 LiLiCorr，这是一种轻量级方法，通过关联并行草稿的似然性来增强连贯性和接受率，展示了比现有方法显著的吞吐量改进。 AI

影响 这些论文推进了加速大型语言模型推理的技术，可能带来更高效、响应更快的 AI 应用。

排序理由 arXiv 上发表了两篇研究论文，详细介绍了大型语言模型推测性解码的新方法和调查。

在 arXiv cs.CL 阅读 →

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新研究探索用于大型语言模型推测性解码的并行草稿

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arXiv 上发表了两篇研究论文，详细介绍了大型语言模型推测性解码的新方法和调查。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Yantao Li, Huanlin Gao, Fang Zhao, Chao Tan, Qiang Hui, Shuting Liu, Fuyuan Shi, Ting Lu, Shaoan Zhao, Xueqiang Guo, Xinpei Su, Jianbing Zhang, Xinyu Dai, Kai Wang, Shiguo Lian ·

    多模态推测解码是否已准备好用于基于扩散的并行草稿生成？一项调查与实证诊断

    arXiv:2608.20743v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by allowing a lightweight drafter to propose future tokens while a target model verifies them in parallel. Its lossless guarantee has motivated a line of work that pushes th…

  2. arXiv cs.CL TIER_1 English(EN) · Matan Rusanovsky, Yoav Miron, Roy Uziel, Omer Belhasin, Ran Zilberstein, Maor Ashkenazi, Michael Elad ·

    LiLiCorr: 轻量级似然相关性用于并行草稿的推测性解码

    arXiv:2608.20530v1 Announce Type: new Abstract: Speculative decoding accelerates language-model inference by drafting future tokens that the target model verifies in parallel. A diffusion-style block head such as DFlash is an attractive drafter, predicting an entire block of futu…

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