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Found 4 papers, 1 papers with code
Making sense of spoken plurals
Our goal is to compare two models for the conceptualization of plurality.
How direct is the link between words and images?
To what extent does this setup rely on visual information from images?
Language with Vision: a Study on Grounded Word and Sentence Embeddings
Our model effectively balances the interplay between language and vision by aligning textual embeddings with visual information while simultaneously preserving the distributional statistics that characterize word usage in text corpora.
Semantic properties of English nominal pluralization: Insights from word embeddings
In comparison with our approach, a method from compositional distributional semantics, called FRACSS, predicted plural vectors that were more similar to the corpus-extracted plural vectors in terms of direction but not vector length.
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