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模型已展现出通过文本提示生成图像的卓越能力，这有助于视觉艺术创作与自我表达中的创造力发挥。然而，生成图像如何精确表达输入文本的语境与情感尚不明确。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准度的方法。受众包编辑策略启发，我们提取了直观的文本特征（如名词数量及具体性），并训练代理模型分析这些特征对AI生成图像的影响。基于代理模型的解释，我们构建了一套调整文本提示的规范，以指导图像生成实现精准的情感表达。通过仿真与用户研究，结果表明RePrompt能显著提升AI生成图像的情感表现力，尤其针对负面情绪的传达。