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English(EN) ForceForget: Reinforcement Concept Removal for Enhancing Safety in Text-to-Image Models

新方法ForceForget增强文本到图像AI模型的安全性

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种名为ForceForget的新方法，以提高文本到图像生成模型的安全性。该方法使用强化学习来优化概念擦除奖励，旨在移除不安全内容，同时不过度抑制良性概念。ForceForget引入了一个安全适配器来调节交叉注意力层中的概念，在防止不安全图像生成的同时保持图像保真度方面表现出有效性，并在鲁棒性和图像到图像场景中优于现有方法。 AI

影响 这项研究提供了一种缓解文本到图像模型不安全内容生成的新方法，有望提高用户安全性和模型实用性。

排序理由 该集群包含一篇详细介绍增强AI模型安全性的新方法的学术论文。

在 arXiv cs.CV 阅读 →

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新方法ForceForget增强文本到图像AI模型的安全性

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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Dong Han, Yong Li ·

    ForceForget：用于增强文本到图像模型安全性的强化概念移除

    arXiv:2606.14351v1 Announce Type: new Abstract: With the advance of generative AI, the text-to-image (T2I) model has the ability to generate various contents. However, T2I models still can generate unsafe contents. To alleviate this issue, various concept erasing methods are prop…

  2. arXiv cs.CV TIER_1 English(EN) · Yong Li ·

    ForceForget：用于增强文本到图像模型安全性的强化概念移除

    With the advance of generative AI, the text-to-image (T2I) model has the ability to generate various contents. However, T2I models still can generate unsafe contents. To alleviate this issue, various concept erasing methods are proposed. However, existing methods tend to excessiv…

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