# Word Embeddings: A Survey

arXiv: https://arxiv.org/abs/1901.09069 · HTML: https://mlsanity.com/paper/1901.09069/

## Key facts

- Cited by 45 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jan 2019.

## Built on by (most cited first, 30 of 45)

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- [Knowledge-Base Enriched Word Embeddings for Biomedical Domain](https://mlsanity.com/paper/2103.00479/) (2021)
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## Abstract (arXiv)

This work lists and describes the main recent strategies for building fixed-length, dense and distributed representations for words, based on the distributional hypothesis. These representations are now commonly called word embeddings and, in addition to encoding surprisingly good syntactic and semantic information, have been proven useful as extra features in many downstream NLP tasks.