# Trans-gram, Fast Cross-lingual Word-embeddings

arXiv: https://arxiv.org/abs/1601.02502 · HTML: https://mlsanity.com/paper/1601.02502/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jan 2016.

## Built on by (most cited first, 3 of 3)

- [Lightweight Cross-Lingual Sentence Representation Learning](https://mlsanity.com/paper/2105.13856/) (2021)
- [Cross-lingual Word Embeddings in Hyperbolic Space](https://mlsanity.com/paper/2205.01907/) (2022)
- [Domain Curricula for Code-Switched MT at MixMT 2022](https://mlsanity.com/paper/2210.17463/) (2022)

## Abstract (arXiv)

We introduce Trans-gram, a simple and computationally-efficient method to simultaneously learn and align wordembeddings for a variety of languages, using only monolingual data and a smaller set of sentence-aligned data. We use our new method to compute aligned wordembeddings for twenty-one languages using English as a pivot language. We show that some linguistic features are aligned across languages for which we do not have aligned data, even though those properties do not exist in the pivot language. We also achieve state of the art results on standard cross-lingual text classification and word translation tasks.