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English(EN) Infrared Organization and Critical Cognitive Field Formation in Transformer Dynamics

新理论表明红外组织控制着大型语言模型中的Transformer动力学

一篇新论文提出,大型语言模型中的涌现行为是由一种涉及时间尺度态密度(TDOS)重组的物理机制所控制。研究人员使用Pythia语言模型从Transformer层雅可比矩阵中提取了弛豫谱,揭示了慢弛豫模式的渐进积累。这一过程导致了无标度记忆核和记忆自能的瞬时最大值,表明红外慢模组织是Transformer动力学中的一个普遍原理。 AI

影响 提出了Transformer动力学的一个普遍原理,可能指导未来的LLM架构和训练。

排序理由 该集群包含一篇学术论文,详细介绍了关于大型语言模型内部动力学的新理论框架和实验发现。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新理论表明红外组织控制着大型语言模型中的Transformer动力学

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该集群包含一篇学术论文,详细介绍了关于大型语言模型内部动力学的新理论框架和实验发现。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Byung Gyu Chae ·

    Transformer动力学中的红外组织与关键认知场形成

    arXiv:2607.10923v1 Announce Type: new Abstract: Large language models exhibit remarkable emergent behaviors, yet the physical mechanism governing their collective dynamics remains poorly understood. Cognitive Field Theory predicts that learning reorganizes the time-scale density …