# Deep Investigation of Cross-Language Plagiarism Detection Methods

arXiv: https://arxiv.org/abs/1705.08828 · HTML: https://mlsanity.com/paper/1705.08828/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 May 2017.

## Built on by (most cited first, 1 of 1)

- [FOCUS: Forging Originality through Contrastive Use in Self-Plagiarism for Language Models](https://mlsanity.com/paper/2406.00839/) (2024)

## Abstract (arXiv)

This paper is a deep investigation of cross-language plagiarism detection methods on a new recently introduced open dataset, which contains parallel and comparable collections of documents with multiple characteristics (different genres, languages and sizes of texts). We investigate cross-language plagiarism detection methods for 6 language pairs on 2 granularities of text units in order to draw robust conclusions on the best methods while deeply analyzing correlations across document styles and languages.