# IndT5: A Text-to-Text Transformer for 10 Indigenous Languages

arXiv: https://arxiv.org/abs/2104.07483 · HTML: https://mlsanity.com/paper/2104.07483/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 29 references that are in the map.
- First posted on arXiv 4 Apr 2021.

## Builds on (most cited first, 17 of 17)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [Distilling the Knowledge in a Neural Network](https://mlsanity.com/paper/1503.02531/) (2015)
- [Neural Machine Translation of Rare Words with Subword Units](https://mlsanity.com/paper/1508.07909/) (2015)
- [Improving Neural Machine Translation Models with Monolingual Data](https://mlsanity.com/paper/1511.06709/) (2015)
- [Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates](https://mlsanity.com/paper/1804.10959/) (2018)
- [Transfer Learning for Low-Resource Neural Machine Translation](https://mlsanity.com/paper/1604.02201/) (2016)
- [Revisiting Low-Resource Neural Machine Translation: A Case Study](https://mlsanity.com/paper/1905.11901/) (2019)
- [Transfer Learning across Low-Resource, Related Languages for Neural Machine Translation](https://mlsanity.com/paper/1708.09803/) (2017)
- [Trivial Transfer Learning for Low-Resource Neural Machine Translation](https://mlsanity.com/paper/1809.00357/) (2018)
- [Language Model Prior for Low-Resource Neural Machine Translation](https://mlsanity.com/paper/2004.14928/) (2020)
- [Challenges of language technologies for the indigenous languages of the Americas](https://mlsanity.com/paper/1806.04291/) (2018)
- [Handling Syntactic Divergence in Low-resource Machine Translation](https://mlsanity.com/paper/1909.00040/) (2019)
- [Translating Similar Languages: Role of Mutual Intelligibility in Multilingual Transformers](https://mlsanity.com/paper/2011.05037/) (2020)
- [Translating the Unseen? Yoruba-English MT in Low-Resource, Morphologically-Unmarked Settings](https://mlsanity.com/paper/2103.04225/) (2021)
- [Towards Neural Machine Translation for Edoid Languages](https://mlsanity.com/paper/2003.10704/) (2020)

## Built on by (most cited first, 10 of 10)

- [The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation](https://mlsanity.com/paper/2106.03193/) (2021)
- [AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing](https://mlsanity.com/paper/2108.05542/) (2021)
- [Evaluation of Transfer Learning for Polish with a Text-to-Text Model](https://mlsanity.com/paper/2205.08808/) (2022)
- [TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese](https://mlsanity.com/paper/2401.16640/) (2024)
- [Neural Machine Translation for the Indigenous Languages of the Americas: An Introduction](https://mlsanity.com/paper/2306.06804/) (2023)
- [Improving Neural Machine Translation of Indigenous Languages with Multilingual Transfer Learning](https://mlsanity.com/paper/2205.06993/) (2022)
- [Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-Mixtec](https://mlsanity.com/paper/2305.17404/) (2023)
- [NLP Progress in Indigenous Latin American Languages](https://mlsanity.com/paper/2404.05365/) (2024)
- [Improving Indigenous Language Machine Translation with Synthetic Data and Language-Specific Preprocessing](https://mlsanity.com/paper/2601.03135/) (2026)
- [Machine Translation of Low-Resource Indo-European Languages](https://mlsanity.com/paper/2108.03739/) (2021)

## Abstract (arXiv)

Transformer language models have become fundamental components of natural language processing based pipelines. Although several Transformer models have been introduced to serve many languages, there is a shortage of models pre-trained for low-resource and Indigenous languages. In this work, we introduce IndT5, the first Transformer language model for Indigenous languages. To train IndT5, we build IndCorpus--a new dataset for ten Indigenous languages and Spanish. We also present the application of IndT5 to machine translation by investigating different approaches to translate between Spanish and the Indigenous languages as part of our contribution to the AmericasNLP 2021 Shared Task on Open Machine Translation. IndT5 and IndCorpus are publicly available for research