Generative AI models have shown impressive ability to produce images with text prompts, which could benefit creativity in visual art creation and self-expression. However, it is unclear how precisely the generated images express contexts and emotions from the input texts. We explored the emotional expressiveness of AI-generated images and developed RePrompt, an automatic method to refine text prompts toward precise expression of the generated images. Inspired by crowdsourced editing strategies, we curated intuitive text features, such as the number and concreteness of nouns, and trained a proxy model to analyze the feature effects on the AI-generated image. With model explanations of the proxy model, we curated a rubric to adjust text prompts to optimize image generation for precise emotion expression. We conducted simulation and user studies, which showed that RePrompt significantly improves the emotional expressiveness of AI-generated images, especially for negative emotions.

翻译：摘要：生成式AI模型展现出通过文本提示生成图像的惊人能力，这种能力有望促进视觉艺术创作与自我表达中的创造力。然而，这些生成图像在多大程度上能精准表达输入文本中的情境与情感尚不明确。我们探究了AI生成图像的情感表现力，并开发了RePrompt——一种自动优化文本提示以提升生成图像表达精确度的方法。受众包编辑策略启发，我们提炼了直观的文本特征（如名词数量与具体性），训练代理模型分析这些特征对AI生成图像的影响。基于代理模型的可解释性分析，我们制定了提示调整规则以优化图像生成中的精确情感表达。通过模拟实验与用户研究，结果表明RePrompt能显著提升AI生成图像的情感表现力，尤其对消极情感的传达效果改善更为显著。