# Analyzing the Surprising Variability in Word Embedding Stability Across Languages

arXiv: https://arxiv.org/abs/2004.14876 · HTML: https://mlsanity.com/paper/2004.14876/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Apr 2020.

## Built on by (most cited first, 7 of 7)

- [Shared Global and Local Geometry of Language Model Embeddings](https://mlsanity.com/paper/2503.21073/) (2025)
- [Evaluating the Construct Validity of Text Embeddings with Application to Survey Questions](https://mlsanity.com/paper/2202.09166/) (2022)
- [A Greek Parliament Proceedings Dataset for Computational Linguistics and Political Analysis](https://mlsanity.com/paper/2210.12883/) (2022)
- [Language Identification for Austronesian Languages](https://mlsanity.com/paper/2206.04327/) (2022)
- [Predicting Embedding Reliability in Low-Resource Settings Using Corpus Similarity Measures](https://mlsanity.com/paper/2206.04330/) (2022)
- [Variation and Instability in Dialect-Based Embedding Spaces](https://mlsanity.com/paper/2303.14963/) (2023)
- [The Prediction-Measurement Gap: Toward Meaning Representations as Scientific Instruments](https://mlsanity.com/paper/2603.10130/) (2026)

## Abstract (arXiv)

Word embeddings are powerful representations that form the foundation of many natural language processing architectures, both in English and in other languages. To gain further insight into word embeddings, we explore their stability (e.g., overlap between the nearest neighbors of a word in different embedding spaces) in diverse languages. We discuss linguistic properties that are related to stability, drawing out insights about correlations with affixing, language gender systems, and other features. This has implications for embedding use, particularly in research that uses them to study language trends.