mlsanityData to 7 Oct 2026

Identifying Machine-Paraphrased Plagiarism

arXiv 2103.11909 ↗First posted 22 Mar 2021cs.CL cs.AI cs.DLcited by 16

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Abstract (arXiv)

Employing paraphrasing tools to conceal plagiarized text is a severe threat to academic integrity. To enable the detection of machine-paraphrased text, we evaluate the effectiveness of five pre-trained word embedding models combined with machine-learning classifiers and eight state-of-the-art neural language models. We analyzed preprints of research papers, graduation theses, and Wikipedia articles, which we paraphrased using different configurations of the tools SpinBot and SpinnerChief. The best-performing technique, Longformer, achieved an average F1 score of 81.0% (F1=99.7% for SpinBot and F1=71.6% for SpinnerChief cases), while human evaluators achieved F1=78.4% for SpinBot and F1=65.6% for SpinnerChief cases. We show that the automated classification alleviates shortcomings of widely-used text-matching systems, such as Turnitin and PlagScan. To facilitate future research, all data, code, and two web applications showcasing our contributions are openly available at https://github.com/jpwahle/iconf22-paraphrase.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 28 of its 55 references that are in the map. First posted on arXiv 22 Mar 2021.

Builds on

28 of 55 references.

References · 28

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 6; 2023: 2; 2024: 4; 2025: 0; 2026: 1.

16 papers.

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  1. 2022How Large Language Models are Transforming Machine-Paraphrased Plagiarismcited by 38
  2. 2024Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challengescited by 18
  3. 2021Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detectioncited by 17
  4. 2022A Domain-adaptive Pre-training Approach for Language Bias Detection in Newscited by 16
  5. 2022Specialized Document Embeddings for Aspect-based Similarity of Research Paperscited by 12
  6. 2023Paraphrase Detection: Human vs. Machine Contentcited by 12
  7. 2021Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detectioncited by 10
  8. 2023Toxicity Detection is NOT all you Need: Measuring the Gaps to Supporting Volunteer Content Moderatorscited by 10
  9. 2021Incorporating Word Sense Disambiguation in Neural Language Modelscited by 6
  10. 2024Survey on Plagiarism Detection in Large Language Models: The Impact of ChatGPT and Gemini on Academic Integritycited by 5
  11. 2024Evaluation of pretrained language models on music understandingcited by 4
  12. 2022Analyzing Multi-Task Learning for Abstractive Text Summarizationcited by 3
4 more
  1. 2022CS-Insights: A System for Analyzing Computer Science Researchcited by 2
  2. 2026The Appeal and Reality of Recycling LoRAs with Adaptive Mergingcited by 2
  3. 2022Investigating the detection of Tortured Phrases in Scientific Literaturecited by 1
  4. 2024Discourse Features Enhance Detection of Document-Level Machine-Generated Contentcited by 1