mlsanityData to 13 Oct 2026

Leveraging Large Models to Evaluate Novel Content: A Case Study on Advertisement Creativity

arXiv 2503.00046 ↗First posted 26 Feb 2025cs.CV cs.AIcited by 0

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Abstract (arXiv)

Evaluating creativity is challenging, even for humans, not only because of its subjectivity but also because it involves complex cognitive processes. Inspired by work in marketing, we attempt to break down visual advertisement creativity into atypicality and originality. With fine-grained human annotations on these dimensions, we propose a suite of tasks specifically for such a subjective problem. We also evaluate the alignment between state-of-the-art (SoTA) vision language models (VLMs) and humans on our proposed benchmark, demonstrating both the promises and challenges of using VLMs for automatic creativity assessment.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 13 of its 40 references that are in the map. First posted on arXiv 26 Feb 2025.

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13 of 40 references.

References · 13

  1. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,831
  2. 2024How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suitescited by 1,041
  3. 2022Towards a Unified Multi-Dimensional Evaluator for Text Generationcited by 264
  4. 2023Art or Artifice? Large Language Models and the False Promise of Creativitycited by 168
  5. 2023TIGERScore: Towards Building Explainable Metric for All Text Generation Taskscited by 69
  6. 2017Automatic Understanding of Image and Video Advertisementscited by 68
  7. 2024AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Textcited by 40
  8. 2024Benchmarking Language Model Creativity: A Case Study on Code Generationcited by 38
  9. 2023I Spy a Metaphor: Large Language Models and Diffusion Models Co-Create Visual Metaphorscited by 31
  10. 2023Probing the Creativity of Large Language Models: Can models produce divergent semantic association?cited by 31
  11. 2024Pron vs Prompt: Can Large Language Models already Challenge a World-Class Fiction Author at Creative Text Writing?cited by 26
  12. 2024CS4: Measuring the Creativity of Large Language Models Automatically by Controlling the Number of Story-Writing Constraintscited by 22
1 more
  1. 2024Every Answer Matters: Evaluating Commonsense with Probabilistic Measurescited by 6

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  1. 2025Creativity Benchmark: A benchmark for marketing creativity for large language models
  2. 2026How LLMs See Creativity: Zero-Shot Scoring of Visual Creativity with Interpretable Reasoning
  3. 2025Stable diffusion models reveal a persisting human and AI gap in visual creativity
  4. 2025CreativityPrism: A Cross-Domain Evaluation Framework for Large Language Model Creativity
  5. 2025CreBench: Human-Aligned Creativity Evaluation from Idea to Process to Product
  6. 2025CREward: A Type-Specific Creativity Reward Model
  7. 2025Probing and Inducing Combinational Creativity in Vision-Language Models
  8. 2025Creation-MMBench: Assessing Context-Aware Creative Intelligence in MLLM