Metraipolis › archive › dc_3149eb3bf511

PlagiaCorpus: A Bilingual, Adversarial, and Cross-Lingual Dataset for Forensic Plagiarism Detection — arXiv:2611.02940

Source: arXiv (en)
Original: https://arxiv.org/abs/2611.02940
License (as archived): CC0-1.0
Archived: 2026-11-03T10:38:02.892Z
SHA-256 of the archived text: b1a7de9c1553089554f15bc90bfa481aff44c110e264303db3a6ecf792386897
Stable URL of this page: https://metraipolis.com/documento/dc_3149eb3bf511

How to cite

PlagiaCorpus: A Bilingual, Adversarial, and Cross-Lingual Dataset for Forensic Plagiarism Detection — arXiv:2611.02940 — arXiv (en), https://arxiv.org/abs/2611.02940 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_3149eb3bf511 (Metraipolis archive dc_3149eb3bf511, sha256 b1a7de9c1553089554f15bc90bfa481aff44c110e264303db3a6ecf792386897)

BibTeX

@misc{dc3149eb3bf511,
  title = {PlagiaCorpus: A Bilingual, Adversarial, and Cross-Lingual Dataset for Forensic Plagiarism Detection — arXiv:2611.02940},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2611.02940},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_3149eb3bf511; sha256 b1a7de9c1553089554f15bc90bfa481aff44c110e264303db3a6ecf792386897},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.02940. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

PlagiaCorpus is a bilingual Arabic-English dataset for benchmarking plagiarism and text-reuse detection, including reuse produced by large language models (LLMs) and reuse across languages. It contains 198,643 text records: a source corpus of 34,885 passages drawn from English and Arabic Wikipedia and two openly licensed book collections, and 163,758 queries (147,381 for training and 16,377 for testing). The queries cover five reuse classes of increasing difficulty, namely verbatim copying, character-level obfuscation, same-language paraphrasing by two different LLMs, and English--Arabic translation with structural paraphrasing, together with a Safe class of non-reused passages. Every positive query is linked to its source passage, and the train/test split is grouped by source passage so that no passage contributes queries to both splits. The release was curated through language identification, removal of LLM generation artefacts, and exact and cross-lingual de-duplication. Technical validation reports per-class length statistics, automatic checks of the train/test split, and inter-annotator agreement on a manually rated sample. The dataset is distributed in JSON and Parquet formats under a CC BY-SA 4.0 license.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv cs.AI, nuovi lavori del giorno).
Categorie arXiv: Computation and Language (cs.CL) ; Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Digital Libraries (cs.DL); Information Retrieval (cs.IR).
Pagina del lavoro: https://arxiv.org/abs/2611.02940 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-11-03T10:29:48.914Z dalla pagina https://arxiv.org/list/cs.AI/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).