A study from the University of California, Berkeley, reveals that large language models significantly decrease the quality of images generated by DALL-E 3 after automatic prompt modifications, with a decline of 58%. Through online experiments comparing DALL-E 2, DALL-E 3, and DALL-E 3 with automatic prompt revisions, it was found that DALL-E 3 outperformed DALL-E 2 in technical capability and adaptability to user prompt strategies. The study noted that DALL-E 3 users achieved better image matching through longer, semantically similar, and more descriptive prompts.