# StyloMetrix: An Open-Source Multilingual Tool for Representing Stylometric Vectors

arXiv: https://arxiv.org/abs/2309.12810 · HTML: https://mlsanity.com/paper/2309.12810/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 52 references that are in the map.
- First posted on arXiv 22 Sep 2023.

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

- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Enriching Word Vectors with Subword Information](https://mlsanity.com/paper/1607.04606/) (2016)
- [Distributed Representations of Sentences and Documents](https://mlsanity.com/paper/1405.4053/) (2014)
- [A Benchmark Dataset for Learning to Intervene in Online Hate Speech](https://mlsanity.com/paper/1909.04251/) (2019)
- [DALEX: explainers for complex predictive models](https://mlsanity.com/paper/1806.08915/) (2018)
- [Going Extreme: Comparative Analysis of Hate Speech in Parler and Gab](https://mlsanity.com/paper/2201.11770/) (2022)
- [The Grammar and Syntax Based Corpus Analysis Tool For The Ukrainian Language](https://mlsanity.com/paper/2305.13530/) (2023)

## Built on by (most cited first, 14 of 14)

- [Bielik 7B v0.1: A Polish Language Model -- Development, Insights, and Evaluation](https://mlsanity.com/paper/2410.18565/) (2024)
- [Pap2Pat: Benchmarking Outline-Guided Long-Text Patent Generation with Patent-Paper Pairs](https://mlsanity.com/paper/2410.07009/) (2024)
- [Bielik v3 Small: Technical Report](https://mlsanity.com/paper/2505.02550/) (2025)
- [Tuning for TraceTarnish: Techniques, Trends, and Testing Tangible Traits](https://mlsanity.com/paper/2512.03465/) (2025)
- [Bielik 11B v2 Technical Report](https://mlsanity.com/paper/2505.02410/) (2025)
- [Can AI-Generated Persuasion Be Detected? Persuaficial Benchmark and AI vs. Human Linguistic Differences](https://mlsanity.com/paper/2601.04925/) (2026)
- [Jako Tako or Fluent? Presenting PoVisLE: A Polish Vision-Language Evaluation](https://mlsanity.com/paper/2608.07763/) (2026)
- [Gram2Vec: An Interpretable Document Vectorizer](https://mlsanity.com/paper/2406.12131/) (2024)
- [Stylometry recognizes human and LLM-generated texts in short samples](https://mlsanity.com/paper/2507.00838/) (2025)
- [StylOch at PAN: Gradient-Boosted Trees with Frequency-Based Stylometric Features](https://mlsanity.com/paper/2507.12064/) (2025)
- [Solving cold start in news recommendations: a RippleNet-based system for large scale media outlet](https://mlsanity.com/paper/2511.02052/) (2025)
- [Large Language Models and Forensic Linguistics: Navigating Opportunities and Threats in the Age of Generative AI](https://mlsanity.com/paper/2512.06922/) (2025)
- [Explaining Generalization of AI-Generated Text Detectors Through Linguistic Analysis](https://mlsanity.com/paper/2601.07974/) (2026)
- [LogicTree-RAG: Logic Tree-guided Retrieval-Augmented Generation for Long-form Patent Drafting](https://mlsanity.com/paper/2609.30943/) (2026)

## Abstract (arXiv)

This work aims to provide an overview on the open-source multilanguage tool called StyloMetrix. It offers stylometric text representations that cover various aspects of grammar, syntax and lexicon. StyloMetrix covers four languages: Polish as the primary language, English, Ukrainian and Russian. The normalized output of each feature can become a fruitful course for machine learning models and a valuable addition to the embeddings layer for any deep learning algorithm. We strive to provide a concise, but exhaustive overview on the application of the StyloMetrix vectors as well as explain the sets of the developed linguistic features. The experiments have shown promising results in supervised content classification with simple algorithms as Random Forest Classifier, Voting Classifier, Logistic Regression and others. The deep learning assessments have unveiled the usefulness of the StyloMetrix vectors at enhancing an embedding layer extracted from Transformer architectures. The StyloMetrix has proven itself to be a formidable source for the machine learning and deep learning algorithms to execute different classification tasks.