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CreBench: Human-Aligned Creativity Evaluation from Idea to Process to Product

AAAI 2026 · Vision-language and multimodal › Multimodal LLMs · approach: Interleaved image-text generation with MLLMs · 1 citations (OpenAlex)

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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

Surprising findings

Limitations

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

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