Research map / Vision-language and multimodal / Multimodal LLMs
CreBench: Human-Aligned Creativity Evaluation from Idea to Process to Product
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Introduces CreBench, a 12-indicator creativity evaluation benchmark (idea, process, product) with the CreMIT instruction-tuning dataset, and fine-tunes LLaVA-1.5-7B into CreExpert, which outperforms GPT-4V and Gemini-Pro-Vision on human-aligned creativity scoring.
Problem
MLLMs struggle to assess human-defined, abstract and subjective creativity in open-ended visual design tasks, and no benchmark exists for multimodal creativity evaluation aligned with human judgments.
Approach
Decompose creativity into idea, process and product dimensions with 12 expert-rated indicators, convert expert feedback into multi-type GPT-4o instruction data, and instruction-tune an open MLLM (LLaVA-1.5-7B) into a creativity evaluation expert.
Key results
- CreExpert achieves overall score 65.50% vs 29.27% for GPT-4V and 27.78% for Gemini-Pro-Vision on CreBench (Pearson-based).
- CreExpert surpasses its LLaVA-1.5-7B baseline by roughly 45 points overall (65.50% vs 20.57%).
- Inter-rater reliability reported as average Fleiss' kappa 0.71 and ICC(2,1) 0.78 among expert annotators.
Surprising findings
- Product-level scores remain low even for CreExpert (about 40% average), with Manufacturability and Novelty gains varying across tasks and a slight drop on Reach.
Limitations
- Evaluation limited to four drawing-based tasks with secondary students, limiting generalizability.
- Only 50/50 split of a small 2.2K-instance dataset used for fine-tuning and evaluation.
- Instruction data generated by GPT-4o from expert feedback may inherit its biases.
Experimental setup
Datasets: CreMIT (CreBench training split)
Benchmarks: CreBench
Metrics: Pearson correlation coefficient
Baselines: GPT-4V Gemini-Pro-Vision mPLUG-Owl2 InstructBLIP Seed1.5-VL Qwen2.5-VL MiniGPT-v2 GLM MiniGPT-4 TinyGPT LLaVA-1.5-7B
Builds on: LLaVA-1.5 Vicuna CLIP LLaMA-Factory
Closest papers by meaning
- CREval: An Automated Interpretable Evaluation for Creative Image Manipulation under Complex Instructions (CVPR 2026 · similarity 0.87)
- Redefining <Creative> in Dictionary: Towards an Enhanced Semantic Understanding of Creative Generation (CVPR 2025 · similarity 0.86)
- IDEAFix: Evaluation Framework for Creative Defixation Prompting in LLMs (NeurIPS 2026 · similarity 0.86)
- AI as Humanity’s Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text (ICLR 2025 · similarity 0.86)
- IDEA-Bench: How Far are Generative Models from Professional Designing? (CVPR 2025 · similarity 0.85)
- CLAWS:Creativity detection for LLM-generated solutions using Attention Window of Sections (NeurIPS 2025 · similarity 0.85)
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