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English(EN) Hierarchical Concept Geometry in Language Models Emerges from Word Co-occurrence

语言模型中的概念几何源于词语共现

一篇新的研究论文提出了一个分布理论,解释了像“is-a”关系这样的分层概念如何在语言模型中以几何方式表示。研究表明,词语共现统计数据的谱组织自然地导致了嵌入中的分层分裂几何。这种现象在word2vec嵌入中被观察到,并且也扩展到了Gemma 2B的解嵌入,这表明复杂的概念层次结构可以从基本的统计模式中涌现,而无需专门的机制。 AI

影响 解释了LLM中的概念层次结构如何从统计词语模式中涌现,可能简化未来的模型设计。

排序理由 学术论文,详细介绍了对语言模型中概念表示的理论和实证分析。

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

语言模型中的概念几何源于词语共现

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学术论文,详细介绍了对语言模型中概念表示的理论和实证分析。
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Andres Nava, Matthieu Wyart ·

    语言模型中的分层概念几何源于词语共现

    arXiv:2605.23821v1 Announce Type: new Abstract: We propose a distributional theory of how hypernymy -- the ``is-a'' relation between general and specific concepts -- is encoded geometrically in language representations. Starting from the empirically verified assumption that words…

  2. arXiv cs.CL TIER_1 English(EN) · Matthieu Wyart ·

    语言模型中的分层概念几何源于词语共现

    We propose a distributional theory of how hypernymy -- the ``is-a'' relation between general and specific concepts -- is encoded geometrically in language representations. Starting from the empirically verified assumption that words closer on the WordNet hypernym graph co-occur m…