---
id: 20260312-T0-13
title: "研究通过神经细胞自动机训练语言模型"
title_en: "Training Language Models via Neural Cellular Automata"
url: https://ai.daily.yangsir.net/daily/20260312-T0-13
issue_date: 2026-03-12
publish_date: 2026-03-12T04:00:00.000Z
category: research
source_name: "arXiv cs.LG (ML)"
source_url: https://arxiv.org/abs/2603.10055
---

# 研究通过神经细胞自动机训练语言模型

arXiv论文2603.10055提出使用神经细胞自动机训练语言模型的新方法，解决传统预训练数据质量有限、存在偏见和知识纠缠问题。该研究探索局部交互机制如何构建全局语言能力，为大模型训练提供新思路，实验结果表明其在特定任务上表现优于传统方法。

## English Version

**Training Language Models via Neural Cellular Automata**

arXiv:2603.10055 proposes training language models via neural cellular automata, addressing traditional pre-training's data quality limitations, biases, and knowledge entanglement. The research explores how local interactions build global language capabilities, offering new insights for LLM training. Experiments show superior performance on specific tasks.

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**来源**：[arXiv cs.LG (ML)](https://arxiv.org/abs/2603.10055)

**详情页**：https://ai.daily.yangsir.net/daily/20260312-T0-13

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