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: textbackslashurlhttps://raganato.github.io/vwsd/.
Original language | English |
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Title of host publication | Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023) |
Place of Publication | Toronto, Canada |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 2227-2234 |
Number of pages | 8 |
DOIs | |
Publication status | Published - 1 Jul 2023 |