---
id: 20260708-T0-02
title: "Oyster-II：用强化学习让LLM既安全又有用"
title_en: "Oyster-II Uses Reinforcement Learning to Balance LLM Safety and Helpfulness"
url: https://ai.daily.yangsir.net/daily/20260708-T0-02
issue_date: 2026-07-08
publish_date: 2026-07-07T04:00:00.000Z
category: research
source_name: "arXiv cs.AI"
source_url: https://arxiv.org/abs/2607.02914
---

# Oyster-II：用强化学习让LLM既安全又有用

arXiv新论文提出Oyster-II，一种通过强化学习实现LLM建设性安全对齐的方法。不同于传统拒绝式对齐策略（直接拒绝不安全请求），Oyster-II在保证安全的同时维持模型的有用性和可信度。该方法旨在解决安全对齐中常见的“过度拒绝”问题，让模型能更聪明地处理敏感问题，而非简单一刀切。

## English Version

**Oyster-II Uses Reinforcement Learning to Balance LLM Safety and Helpfulness**

A new arXiv paper introduces Oyster-II, a reinforcement learning approach for constructive safety alignment in LLMs. Unlike conventional refusal-oriented strategies that outright reject unsafe requests, Oyster-II maintains safety while preserving helpfulness and trustworthiness. It addresses the over-refusal problem, enabling models to handle sensitive queries more intelligently.

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**来源**：[arXiv cs.AI](https://arxiv.org/abs/2607.02914)

**详情页**：https://ai.daily.yangsir.net/daily/20260708-T0-02

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