# Open Language Data Initiative: Advancing Low-Resource Machine Translation for Karakalpak

arXiv: https://arxiv.org/abs/2409.04269 · HTML: https://mlsanity.com/paper/2409.04269/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 16 references that are in the map.
- First posted on arXiv 6 Sep 2024.

## Builds on (most cited first, 7 of 7)

- [SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing](https://mlsanity.com/paper/1808.06226/) (2018)
- [A Call for Clarity in Reporting BLEU Scores](https://mlsanity.com/paper/1804.08771/) (2018)
- [No Language Left Behind: Scaling Human-Centered Machine Translation](https://mlsanity.com/paper/2207.04672/) (2022)
- [Adafactor: Adaptive Learning Rates with Sublinear Memory Cost](https://mlsanity.com/paper/1804.04235/) (2018)
- [Language-agnostic BERT Sentence Embedding](https://mlsanity.com/paper/2007.01852/) (2020)
- [MADLAD-400: A Multilingual And Document-Level Large Audited Dataset](https://mlsanity.com/paper/2309.04662/) (2023)
- [The first neural machine translation system for the Erzya language](https://mlsanity.com/paper/2209.09368/) (2022)

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

- [GlotEval: A Test Suite for Massively Multilingual Evaluation of Large Language Models](https://mlsanity.com/paper/2504.04155/) (2025)
- [The first open machine translation system for the Chechen language](https://mlsanity.com/paper/2507.12672/) (2025)

## Abstract (arXiv)

This study presents several contributions for the Karakalpak language: a FLORES+ devtest dataset translated to Karakalpak, parallel corpora for Uzbek-Karakalpak, Russian-Karakalpak and English-Karakalpak of 100,000 pairs each and open-sourced fine-tuned neural models for translation across these languages. Our experiments compare different model variants and training approaches, demonstrating improvements over existing baselines. This work, conducted as part of the Open Language Data Initiative (OLDI) shared task, aims to advance machine translation capabilities for Karakalpak and contribute to expanding linguistic diversity in NLP technologies.