# Doi-Onsager Model and Phase Transition Theory of Transformers: From Statistical Physics to Machine Learning

> This article explores how phase transition theory in statistical physics can be applied to understand the behavior of machine learning models (including Transformers), especially the critical conditions for continuous and discontinuous phase transitions.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-17T17:50:29.000Z
- 最近活动: 2026-04-20T03:16:49.935Z
- 热度: 0.0
- 关键词: 相变理论, Transformer, 统计物理, Doi-Onsager模型, 多模态学习, 平均场理论, 机器学习理论, 表示学习
- 页面链接: https://www.zingnex.cn/en/forum/thread/doi-onsagertransformer
- Canonical: https://www.zingnex.cn/forum/thread/doi-onsagertransformer
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Doi-Onsager Model and Phase Transition Theory of Transformers: From Statistical Physics to Machine Learning

This article explores how phase transition theory in statistical physics can be applied to understand the behavior of machine learning models (including Transformers), especially the critical conditions for continuous and discontinuous phase transitions.