# Embedding Learning Through Multilingual Concept Induction

arXiv: https://arxiv.org/abs/1801.06807 · HTML: https://mlsanity.com/paper/1801.06807/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jan 2018.

## Built on by (most cited first, 1 of 1)

- [Massively Multilingual Text Translation For Low-Resource Languages](https://mlsanity.com/paper/2401.16582/) (2024)

## Abstract (arXiv)

We present a new method for estimating vector space representations of words: embedding learning by concept induction. We test this method on a highly parallel corpus and learn semantic representations of words in 1259 different languages in a single common space. An extensive experimental evaluation on crosslingual word similarity and sentiment analysis indicates that concept-based multilingual embedding learning performs better than previous approaches.