Hifloat4 Format For End To End Reinforcement Learn

---
name: hifloat4-format-for-end-to-end-reinforcement-learn
description: HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models
version: 1.0.0
date: 2026-07-30
arxiv_id: 2607.26515
tags: ["arxiv", "research", "paper", "multi-agent-rl"]
activation_keywords: ["hifloat4", "format", "for", "end", "to"]
---

# HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models

**arXiv ID:** 2607.26515
**Utility Score:** 1.00
**Authors:** Hei Yi Mak, Shadan Golestan, Hoang Le
**URL:** https://arxiv.org/abs/2607.26515

## 概述

HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models

这是一篇来自 arXiv 的高价值论文（utility score: 1.00），通过自动追踪系统识别。

## 核心创新

*待研究论文内容后填写*

## 应用场景

*待研究论文内容后填写*

## 实现要点

*待研究论文内容后填写*

## 参考资源

- [arXiv论文](https://arxiv.org/abs/2607.26515)