# ALL-IN-1: Short Text Classification with One Model for All Languages

arXiv: https://arxiv.org/abs/1710.09589 · HTML: https://mlsanity.com/paper/1710.09589/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Oct 2017.

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

- [Model Stability with Continuous Data Updates](https://mlsanity.com/paper/2201.05692/) (2022)
- [Identifying Banking Transaction Descriptions via Support Vector Machine Short-Text Classification Based on a Specialized Labelled Corpus](https://mlsanity.com/paper/2404.08664/) (2024)

## Abstract (arXiv)

We present ALL-IN-1, a simple model for multilingual text classification that does not require any parallel data. It is based on a traditional Support Vector Machine classifier exploiting multilingual word embeddings and character n-grams. Our model is simple, easily extendable yet very effective, overall ranking 1st (out of 12 teams) in the IJCNLP 2017 shared task on customer feedback analysis in four languages: English, French, Japanese and Spanish.