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This paper describes our zero-shot approaches for the Visual Word Sense Disambiguation (VWSD) Task in English. Our preliminary study shows that the simple approach of matching candidate images with the phrase using CLIP suffers from the many-to-many nature of image-text pairs. We find that the CLIP text encoder may have limited abilities in capturi...
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... then rank the candidate images based on the new probability in descending order, with the highest probability candidate image being the predicted image from the ensembled model. See Table 1. ...Context 2
... Augment-CLIP does not outperform Base-CLIP, often due to poor translation, but, interestingly, it offers sufficient complementarity to Base-CLIP or other Augment-CLIP that it improves performance through ensembling. See results in Table 1. ...Context 3
... the organizers' baseline uses CLIP-ViT-largepatch14-336, an even larger model which improved performance in test data. See Table 1. This leads to the question of how different Base-CLIP embeddings affect performance on this task, which is outside the scope of this paper as we take the Base-CLIP embedding as a given in our systems. ...Similar publications
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