English(EN) Tracing Morphology, Semantics, and Divergence in Language Acquisition

研究追踪大型语言模型在中间训练阶段的语言习得

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-15 04:00

一篇新发表在arXiv上的研究论文，通过检查中间训练检查点，探讨了大型语言模型（LLMs）中语言习得的发展轨迹。该研究利用了Pythia和OLMo等开源模型，分析了形态结构、嵌入漂移、重复主导和共现效应在训练过程中如何演变。主要发现表明，模型在语义嵌入稳定之前显著发展了形态结构，并且训练数据集大小对分歧识别有积极影响，而预训练共现和推理重复则对其产生负面影响。 AI

影响为理解大型语言模型的发展阶段提供了见解，可能指导未来的模型训练和评估策略。

排序理由该集群包含一篇发表在arXiv上的研究论文，详细介绍了大型语言模型语言习得的发现。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CL TIER_1 English(EN) · Forough Shirin Abkenar, Haoshuo Fu, Liang Feng, Ning Yan, Masood S. Mortazavi · 2026-10-15 04:00

语言习得中形态、语义和分化的追踪

arXiv:2610.19041v1 Announce Type: cross Abstract: Understanding the dynamics of language acquisition in Large Language Models (LLMs) is crucial for uncovering how statistical representations evolve into structured linguistic capabilities. However, most existing studies focus prim…

本文如何被排名

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语言习得中形态、语义和分化的追踪

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