mlsanityData to 14 Oct 2026

CAP: Evaluation of Persuasive and Creative Image Generation

arXiv 2412.10426 ↗First posted 10 Dec 2024cs.CV cs.CL cs.GRcited by 5

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Abstract (arXiv)

We address the task of advertisement image generation and introduce three evaluation metrics to assess Creativity, prompt Alignment, and Persuasiveness (CAP) in generated advertisement images. Despite recent advancements in Text-to-Image (T2I) generation and their performance in generating high-quality images for explicit descriptions, evaluating these models remains challenging. Existing evaluation methods focus largely on assessing alignment with explicit, detailed descriptions, but evaluating alignment with visually implicit prompts remains an open problem. Additionally, creativity and persuasiveness are essential qualities that enhance the effectiveness of advertisement images, yet are seldom measured. To address this, we propose three novel metrics for evaluating the creativity, alignment, and persuasiveness of generated images. Our findings reveal that current T2I models struggle with creativity, persuasiveness, and alignment when the input text is implicit messages. We further introduce a simple yet effective approach to enhance T2I models' capabilities in producing images that are better aligned, more creative, and more persuasive.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 32 of its 62 references that are in the map. First posted on arXiv 10 Dec 2024.

Builds on

32 of 62 references.

References · 32

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20 more
  1. 2023Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesiscited by 890
  2. 2023PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesiscited by 864
  3. 2024How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMscited by 573
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  11. 2024Can Language Models Recognize Convincing Arguments?cited by 21
  12. 2024EVALALIGN: Supervised Fine-Tuning Multimodal LLMs with Human-Aligned Data for Evaluating Text-to-Image Modelscited by 20
  13. 2024Measuring and Improving Persuasiveness of Large Language Modelscited by 20
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  15. 2023A Video Is Worth 4096 Tokens: Verbalize Videos To Understand Them In Zero Shotcited by 11
  16. 2024Prompt Optimizer of Text-to-Image Diffusion Models for Abstract Concept Understandingcited by 9
  17. 2024Social Reward: Evaluating and Enhancing Generative AI through Million-User Feedback from an Online Creative Communitycited by 8
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  20. 2018Persuasive Faces: Generating Faces in Advertisementscited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 2.

5 papers.

  1. 2025Culture in Action: Evaluating Text-to-Image Models through Social Activitiescited by 10
  2. 2025Evaluation of Cultural Competence of Vision-Language Modelscited by 3
  3. 2025Towards Generalization of Tactile Image Generation: Reference-Free Evaluation in a Leakage-Free Settingcited by 1
  4. 2026Sense it with your eyes: Sensation Generation and Understanding for Advertisementscited by 0
  5. 2026CogenPVG: Cognitive-Enhanced Reflective Multi-Agent Framework for Persuasive Video Generationcited by 0