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Found 3 papers, 2 papers with code
Skip-gram word embeddings in hyperbolic space
Recent work has demonstrated that embeddings of tree-like graphs in hyperbolic space surpass their Euclidean counterparts in performance by a large margin.
Controlled Experiments for Word Embeddings
The experiments reveal that word vector length depends more or less linearly on both word frequency and the level of noise in the co-occurrence distribution of the word.
Measuring Word Significance using Distributed Representations of Words
Distributed representations of words as real-valued vectors in a relatively low-dimensional space aim at extracting syntactic and semantic features from large text corpora.
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