# Gzip versus bag-of-words for text classification

arXiv: https://arxiv.org/abs/2307.15002 · HTML: https://mlsanity.com/paper/2307.15002/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 6 references that are in the map.
- First posted on arXiv 27 Jul 2023.

## Builds on (most cited first, 1 of 1)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)

## Built on by (most cited first, 2 of 2)

- [Tiny, Hardware-Independent, Compression-based Classification](https://mlsanity.com/paper/2603.06359/) (2026)
- [Text Distance from Nested and Hierarchical Repetitions: A Compression-Based Perspective](https://mlsanity.com/paper/2607.05416/) (2026)

## Abstract (arXiv)

The effectiveness of compression in text classification ('gzip') has recently garnered lots of attention. In this note we show that `bag-of-words' approaches can achieve similar or better results, and are more efficient.