mlsanityData to 14 Oct 2026

A Simple and Effective Method of Cross-Lingual Plagiarism Detection

arXiv 2304.01352 ↗First posted 3 Apr 2023cs.CL cs.IRcited by 0

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Abstract (arXiv)

We present a simple cross-lingual plagiarism detection method applicable to a large number of languages. The presented approach leverages open multilingual thesauri for candidate retrieval task and pre-trained multilingual BERT-based language models for detailed analysis. The method does not rely on machine translation and word sense disambiguation when in use, and therefore is suitable for a large number of languages, including under-resourced languages. The effectiveness of the proposed approach is demonstrated for several existing and new benchmarks, achieving state-of-the-art results for French, Russian, and Armenian languages.

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References · 5

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  3. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 723
  4. 2017Word Translation Without Parallel Datacited by 487
  5. 2017UsingWord Embedding for Cross-Language Plagiarism Detectioncited by 3

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