标题： 更安全的提示：降低视觉生成式人工智能中的知识产权风险 显示英文标题

标题： Safer Prompts: Reducing IP Risk in Visual Generative AI

摘要： 视觉生成AI模型在从简单的文本提示生成高质量图像方面展示了显著的能力。然而，由于这些模型是在来自不同来源的图像上进行训练的，它们可能会记住并再现特定内容，从而引发关于知识产权（IP）侵权的担忧。近期在提示工程方面的进展提供了一种成本效益高的方法来提升生成式AI的性能。在本文中，我们评估了提示工程技术在减轻图像生成中的IP侵权风险方面的有效性。我们的研究结果显示，思维链提示和任务指令提示显著降低了生成图像与扩散模型训练数据之间的相似性，从而降低了IP侵权的风险。 显示英文摘要

摘要： Visual Generative AI models have demonstrated remarkable capability in generating high-quality images from simple inputs like text prompts. However, because these models are trained on images from diverse sources, they risk memorizing and reproducing specific content, raising concerns about intellectual property (IP) infringement. Recent advances in prompt engineering offer a cost-effective way to enhance generative AI performance. In this paper, we evaluate the effectiveness of prompt engineering techniques in mitigating IP infringement risks in image generation. Our findings show that Chain of Thought Prompting and Task Instruction Prompting significantly reduce the similarity between generated images and the training data of diffusion models, thereby lowering the risk of IP infringement.