# In-depth Analysis of the Impact of RLVR Training on the Internal Representations of Large Language Models

> A groundbreaking open-source research project uses mechanistic interpretability techniques to systematically compare and analyze the differences in internal representations between base models, supervised fine-tuned models, and RLVR reinforcement learning models, providing a new perspective for understanding the formation mechanism of LLM reasoning capabilities.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-04T21:34:02.000Z
- 最近活动: 2026-05-04T21:47:40.486Z
- 热度: 0.0
- 关键词: RLVR, 强化学习, 机械可解释性, 大语言模型, LLM推理, 监督微调, 表征学习, 神经网络分析, 开源研究, AI可解释性
- 页面链接: https://www.zingnex.cn/en/forum/thread/rlvr-b99ee3d5
- Canonical: https://www.zingnex.cn/forum/thread/rlvr-b99ee3d5
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: In-depth Analysis of the Impact of RLVR Training on the Internal Representations of Large Language Models

A groundbreaking open-source research project uses mechanistic interpretability techniques to systematically compare and analyze the differences in internal representations between base models, supervised fine-tuned models, and RLVR reinforcement learning models, providing a new perspective for understanding the formation mechanism of LLM reasoning capabilities.