English(EN) Asynchronous Flow Map Language Models

新型异步流图语言模型在一步生成中达到最先进水平

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

研究人员推出了一种新颖的一步并行语言建模方法——异步流图语言模型（aFMLMs），该方法包含预测顺序。与迭代模型不同，aFMLMs学习异步流的流图，该流图规定了控制去噪进度的逐令牌时间表。通过内化学习到的顺序，该方法允许模型在一次前向传播中生成所有令牌。在 Sudoku 求解和 GSM8K 数学问题的代码生成评估中，aFMLMs 在一步建模方面取得了新的最先进性能。 AI

影响引入了一种新颖的一步并行生成方法，有望提高语言模型的效率和性能。

排序理由该集群包含一篇在 arXiv 上发表的关于新语言模型架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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Newsworthiness bucket: Tool; 该集群包含一篇在 arXiv 上发表的关于新语言模型架构的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Chanhyuk Lee, Wonjung Kim, Patrick Pynadath, Jaehoon Yoo, Satoshi Hayakawa, Ruqi Zhang, Jinwoo Kim, Seunghoon Hong · 2026-11-02 05:00

Asynchronous Flow Map Language Models

arXiv:2610.42018v1 Announce Type: new Abstract: The order in which tokens are predicted in language modeling has a profound impact on the quality of generated sequences. Autoregressive and masked diffusion models iteratively fill in tokens and can exploit such orderings across ge…

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Asynchronous Flow Map Language Models

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