Papers with visual-semantic embeddings
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 . |
Learning Visually-Grounded Semantics from Contrastive Adversarial Samples (C18-1)
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| Challenge: | Existing frameworks for grounding distributional representations of texts on the visual domain are limited . effective and efficient grounding of distributional embeddings remains challenging . |
| Approach: | They propose to ground distributional representations of texts on the visual domain using visual-semantic embeddings. |
| Outcome: | The proposed model improves on a diverse set of downstream tasks and defends known-type adversarial attacks. |