Abstract: This paper presents the Visual Word Sense Disambiguation (Visual-WSD) task.The objective of Visual-WSD is to identify among a set of ten images the one that corresponds to the intended meaning of a given ambiguous word which is accompanied with minimal context. The task provides datasets for three different languages: English, Italian, and Farsi.We received a total of 96 different submissions. Out of these, 40 systems outperformed a strong zero-shot CLIP-based baseline.Participating systems proposed different zero- and few-shot approaches, often involving generative models and data augmentation.More information can be found on the task's website: \textbackslash{}url\{https://raganato.github.io/vwsd/\}.