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Language Models as Zero-shot Visual Semantic Learners
We find that contextual representations in language mod-els outperform static word embeddings, when the compositional chain of object is short.
What Remains of Visual Semantic Embeddings
Although different paradigms of visual semantic embedding models are designed to align visual features and distributed word representations, it is unclear to what extent current ZSL models encode semantic information from distributed word representations.
Probabilistic Semantic Embedding
We present an extension of a variational auto-encoder that creates semantically richcoupled probabilistic latent representations that capture the semantics of multiplemodalities of data.
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