SilCC
A visual-stimulus benchmark dataset for evaluating associative creativity, in which the naming difficulty of visual stimuli is modulated through progressively complex combinations of abstract shapes.
Timeline (last 90 days)
The study uses two datasets: SilCC (which modulates naming difficulty through progressively complex abstract shape compositions) and PixCC (which increases recognition difficulty by adding random visual noise) to compare the associative creativity of humans and multimodal large models.
In the SilCC dataset, as naming difficulty increased, the effectiveness of all participants (humans and MLLMs) declined.
All Facts (2)
The study uses two datasets: SilCC (which modulates naming difficulty through progressively complex abstract shape compositions) and PixCC (which increases recognition difficulty by adding random visual noise) to compare the associative creativity of humans and multimodal large models.
50%UnverifiedIn the SilCC dataset, as naming difficulty increased, the effectiveness of all participants (humans and MLLMs) declined.
50%