# Number Theory Meets Linguistics: Modelling Noun Pluralisation Across 1497 Languages Using 2-adic Metrics

arXiv: https://arxiv.org/abs/2211.13124 · HTML: https://mlsanity.com/paper/2211.13124/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 16 references that are in the map.
- First posted on arXiv 8 Oct 2022.

## Builds on (most cited first, 4 of 4)

- [Poincar'e Embeddings for Learning Hierarchical Representations](https://mlsanity.com/paper/1705.08039/) (2017)
- [Poincar'e GloVe: Hyperbolic Word Embeddings](https://mlsanity.com/paper/1810.06546/) (2018)
- [Cross-lingual Word Embeddings in Hyperbolic Space](https://mlsanity.com/paper/2205.01907/) (2022)
- [The Construction and Evaluation of the LEAFTOP Dataset of Automatically Extracted Nouns in 1480 Languages](https://mlsanity.com/paper/2206.05034/) (2022)

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

- [Learning with the p-adics](https://mlsanity.com/paper/2512.22692/) (2025)
- [Continuous Optimization for p-adic Models](https://mlsanity.com/paper/2609.25501/) (2026)

## Abstract (arXiv)

A simple machine learning model of pluralisation as a linear regression problem minimising a p-adic metric substantially outperforms even the most robust of Euclidean-space regressors on languages in the Indo-European, Austronesian, Trans New-Guinea, Sino-Tibetan, Nilo-Saharan, Oto-Meanguean and Atlantic-Congo language families. There is insufficient evidence to support modelling distinct noun declensions as a p-adic neighbourhood even in Indo-European languages.