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MLLMs can outperform humans in target detection and acquisition but fail to mimic the nuanced temporal dynamics of human visual search.
VLMs reveal that people can be looking at different places but still "seeing" the same thing, adding a crucial layer of semantic understanding to traditional eye-tracking analysis.
SPGen accurately predicts human eye movements on paintings by cleverly adapting models trained on natural images, opening new avenues for AI-driven art analysis and preservation.
