# naab: A ready-to-use plug-and-play corpus for Farsi

arXiv: https://arxiv.org/abs/2208.13486 · HTML: https://mlsanity.com/paper/2208.13486/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 32 references that are in the map.
- First posted on arXiv 29 Aug 2022.

## Builds on (most cited first, 10 of 10)

- [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)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models](https://mlsanity.com/paper/2206.04615/) (2022)
- [Datasets: A Community Library for Natural Language Processing](https://mlsanity.com/paper/2109.02846/) (2021)
- [Are Large Pre-Trained Language Models Leaking Your Personal Information?](https://mlsanity.com/paper/2205.12628/) (2022)
- [Towards a Cleaner Document-Oriented Multilingual Crawled Corpus](https://mlsanity.com/paper/2201.06642/) (2022)
- [ParsBERT: Transformer-based Model for Persian Language Understanding](https://mlsanity.com/paper/2005.12515/) (2020)
- [LSCP: Enhanced Large Scale Colloquial Persian Language Understanding](https://mlsanity.com/paper/2003.06499/) (2020)
- [The Challenges of Persian User-generated Textual Content: A Machine Learning-Based Approach](https://mlsanity.com/paper/2101.08087/) (2021)

## Built on by (most cited first, 5 of 5)

- [Matina: A Large-Scale 73B Token Persian Text Corpus](https://mlsanity.com/paper/2502.09188/) (2025)
- [MELAC: Massive Evaluation of Large Language Models with Alignment of Culture in Persian Language](https://mlsanity.com/paper/2508.00673/) (2025)
- [PBBQ: A Persian Bias Benchmark Dataset Curated with Human-AI Collaboration for Large Language Models](https://mlsanity.com/paper/2510.19616/) (2025)
- [PerHalluEval: Persian Hallucination Evaluation Benchmark for Large Language Models](https://mlsanity.com/paper/2509.21104/) (2025)
- [Persian Pixel: A large-scale synthetic OCR dataset for Persian language](https://mlsanity.com/paper/2607.20385/) (2026)

## Abstract (arXiv)

The rise of large language models (LLMs) has transformed numerous natural language processing (NLP) tasks, yet their performance in low and mid-resource languages, such as Farsi, still lags behind resource-rich languages like English. To address this gap, we introduce naab, the largest publicly available, cleaned, and ready-to-use Farsi textual corpus. naab consists of 130GB of data, comprising over 250 million paragraphs and 15 billion words. Named after the Farsi word NAAB (meaning "pure" or "high-grade"), this corpus is openly accessible via Hugging Face, offering researchers a valuable resource for Farsi NLP tasks. In addition to naab, we provide naab-raw, an unprocessed version of the dataset, along with a pre-processing toolkit that allows users to clean their custom corpora. These resources empower NLP researchers and practitioners, particularly those focusing on low-resource languages, to improve the performance of LLMs in their respective domains and bridge the gap between resource-rich and resource-poor languages.