# Inference Trajectory Topology: A New Method for Uncertainty Quantification of Large Language Models Without Calibration

> This article introduces an innovative method called "Inference Trajectory Topology", which achieves uncertainty quantification without additional calibration by analyzing the topological structure of the chain of thought during the reasoning process of large language models, providing new ideas for improving model reliability.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-01T22:09:57.000Z
- 最近活动: 2026-05-01T22:17:31.293Z
- 热度: 0.0
- 关键词: 大语言模型, 不确定性量化, 链式思考, 图论, 模型可靠性, 免校准方法
- 页面链接: https://www.zingnex.cn/en/forum/thread/llm-github-markyx316-llm-reasoning-trace-topology
- Canonical: https://www.zingnex.cn/forum/thread/llm-github-markyx316-llm-reasoning-trace-topology
- Markdown 来源: floors_fallback

---

## Introduction / Main Floor: Inference Trajectory Topology: A New Method for Uncertainty Quantification of Large Language Models Without Calibration

This article introduces an innovative method called "Inference Trajectory Topology", which achieves uncertainty quantification without additional calibration by analyzing the topological structure of the chain of thought during the reasoning process of large language models, providing new ideas for improving model reliability.