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Found 6 papers, 2 papers with code
How to marry a star: probabilistic constraints for meaning in context
In this paper, we derive a notion of 'word meaning in context' that characterizes meaning as both intensional and conceptual.
High-risk learning: acquiring new word vectors from tiny data
Distributional semantics models are known to struggle with small data.
Projection Al\'eatoire Non-N\'egative pour le Calcul de Word Embedding / Non-Negative Randomized Word Embedding
Non-Negative Randomized Word Embedding We propose a word embedding method which is based on a novel random projection technique.
FOIL it! Find One mismatch between Image and Language caption
In this paper, we aim to understand whether current language and vision (LaVi) models truly grasp the interaction between the two modalities.
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