Human-Like Attention? A Psychophysical Comparison of Visual Search in Humans and MLLMs
Visual search is a fundamental cognitive ability. This study investigates whether Multimodal Large Language Models (MLLMs) exhibit human-like difficulty signatures in visual search tasks. We compared search performance of humans (n = 1,250) and MLLMs using identical 2D and 3D stimuli across different set sizes. Both groups showed efficient performance in feature searches, most clearly when the target had a unique color, but performance degradation in conjunction searches as set sizes increased. Additionally, we found strong correlations between human and MLLM error rates ($ρ= 0.82$), which suggests that MLLMs are sensitive to similar objective complexities, such as stimulus heterogeneity....
| Authors | Renchi Zhang, Joost C. F. de Winter, Dimitra Dodou et al. |
|---|---|
| Primary category | cs.HC |
| Published | 4 October 2026 |
| Last updated at source | 4 October 2026 |
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