CREATE: Creativity Evaluation of VLMs using the Visual Remote Associates Test
cs.CL
Submitted: 2026-10-13
Updated: 2026-10-13
Comments: 18 pages, 9 figures
Code: https://github.com/CeYang214/CREATEivity-benchmark
License: http://creativecommons.org/licenses/by/4.0/
The gist: Vision language models (VLMs) are used in creative tasks such as visual storytelling, design ideation, art interpretation, and advertising.
Abstract
Vision language models (VLMs) are used in creative tasks such as visual storytelling, design ideation, art interpretation, and advertising. Yet we lack principled ways to measure the lateral reasoning of these models compared to human potential. We introduce CREATE, a semi-automatically constructed benchmark containing 155 visual Remote Associates Test problems. These problems require a solver to find an underlying connection among three seemingly dissimilar images. We conduct a human study (N=25) to validate and ground the quality of our benchmark, and evaluate 11 VLMs. Our findings show that most VLMs underperform humans on this task. Our experiments indicate that the associative ability of VLMs depends on the cue concepts provided in the text and does not universally extend to visual puzzles.
Sources
- Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding
- DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression
- Are Language Models Puzzle Prodigies? Algorithmic Puzzles Unveil Serious Challenges in Multimodal Reasoning
- InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
- Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World
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