Papers by Suna Bensch

1 papers
Probing Multimodal Embeddings for Linguistic Properties: the Visual-Semantic Case (2020.coling-main)

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Challenge: Semantic embeddings have advanced the state of the art for natural language processing tasks . but their inner workings are poorly understood and there is a shortage of analysis tools .
Approach: They propose to extend visual-semantic embeddings to multimodal domains by defining probing tasks for embeddable image-caption pairs and testing them with classifiers.
Outcome: The proposed probing tasks show up to 16% more accurate on visual-semantic embeddings compared to unimodal embedders . the proposed extensions to multimodal domains have been lauded as promising in natural language processing .

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