GloVe vs Word2Vec.

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Answer

$GloVe (Pennington 2014): explicit weighted matrix factorization of log co-occurrence counts.$
$\operatorname{log}(X_{\mathrm{ij}})$
$Batch training on global statistics (vs Word2Vec's per-window streaming).$
$Similar quality to Word2Vec; GloVe often better on analogy tasks, Word2Vec on similarity.$
$Modern: both superseded by contextual embeddings (BERT / sentence-transformers).$
$Still cited in interview questions.$

Check yourself — multiple choice

Same thing
GloVe: explicit weighted log-co-occurrence factorization (global stats); Word2Vec: local windows; similar quality, both superseded by contextual embeddings
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GloVe: global log co-occurrence factorization; Word2Vec: local windows.

#representation-learning#nlp

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