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.

翻译：我们提出了一种适用于大量语言的简单的跨语言抄袭检测方法。所提出的方法利用公开的多语言词库进行候选项检索任务，并利用预训练的基于BERT的多语言语言模型进行详细分析。该方法在使用过程中不依赖机器翻译和词义消歧，因此适用于大量语言，包括资源匮乏的语言。所提出的方法的有效性针对多个现有和新的基准进行了展示，在法语、俄语和亚美尼亚语等语言上取得了最先进的结果。