mlsanityData to 7 Oct 2026

CHEAT: A Large-scale Dataset for Detecting ChatGPT-writtEn AbsTracts

arXiv 2304.12008 ↗First posted 24 Apr 2023cs.CLcited by 39

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Abstract (arXiv)

The powerful ability of ChatGPT has caused widespread concern in the academic community. Malicious users could synthesize dummy academic content through ChatGPT, which is extremely harmful to academic rigor and originality. The need to develop ChatGPT-written content detection algorithms call for large-scale datasets. In this paper, we initially investigate the possible negative impact of ChatGPT on academia,and present a large-scale CHatGPT-writtEn AbsTract dataset (CHEAT) to support the development of detection algorithms. In particular, the ChatGPT-written abstract dataset contains 35,304 synthetic abstracts, with Generation, Polish, and Mix as prominent representatives. Based on these data, we perform a thorough analysis of the existing text synthesis detection algorithms. We show that ChatGPT-written abstracts are detectable, while the detection difficulty increases with human involvement.Our dataset is available in https://github.com/botianzhe/CHEAT.

Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). Builds on 23 of its 46 references that are in the map. First posted on arXiv 24 Apr 2023.

Builds on

23 of 46 references.

References · 23

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
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  5. 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
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  7. 2023DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvaturecited by 705
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  11. 2019GLTR: Statistical Detection and Visualization of Generated Textcited by 490
  12. 2023Is ChatGPT a General-Purpose Natural Language Processing Task Solver?cited by 486
11 more
  1. 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 472
  2. 2019Automatic Detection of Generated Text is Easiest when Humans are Fooledcited by 260
  3. 2023Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Studycited by 203
  4. 2023GPT detectors are biased against non-native English writerscited by 175
  5. 2023Is ChatGPT better than Human Annotators? Potential and Limitations of ChatGPT in Explaining Implicit Hate Speechcited by 165
  6. 2023Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERTcited by 155
  7. 2023Towards Making the Most of ChatGPT for Machine Translationcited by 138
  8. 2023ChatGPT or Human? Detect and Explain. Explaining Decisions of Machine Learning Model for Detecting Short ChatGPT-generated Textcited by 84
  9. 2023Will ChatGPT get you caught? Rethinking of Plagiarism Detectioncited by 41
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Citing papers per year: 2023: 11; 2024: 12; 2025: 9; 2026: 7.

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  1. 2023Can LLM-Generated Misinformation Be Detected?cited by 173
  2. 2023Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Taskscited by 102
  3. 2023A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directionscited by 101
  4. 2023A Survey on Detection of LLMs-Generated Contentcited by 70
  5. 2024DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarioscited by 37
  6. 2023A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Textscited by 23
  7. 2024Detecting AI-Generated Text: Factors Influencing Detectability with Current Methodscited by 23
  8. 2023The Age of Synthetic Realities: Challenges and Opportunitiescited by 15
  9. 2023Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyondcited by 14
  10. 2023Detecting ChatGPT: A Survey of the State of Detecting ChatGPT-Generated Textcited by 10
  11. 2025Reliably Bounding False Positives: A Zero-Shot Machine-Generated Text Detection Framework via Multiscaled Conformal Predictioncited by 10
  12. 2023Playing with words: Comparing the vocabulary and lexical diversity of ChatGPT and humanscited by 8
27 more
  1. 2024GenAI Content Detection Task 2: AI vs. Human -- Academic Essay Authenticity Challengecited by 6
  2. 2024Survey on Plagiarism Detection in Large Language Models: The Impact of ChatGPT and Gemini on Academic Integritycited by 5
  3. 2024Measuring Human Contribution in AI-Assisted Content Generationcited by 5
  4. 2025Large Language Model Sourcing: A Surveycited by 5
  5. 2025The Arabic AI Fingerprint: Stylometric Analysis and Detection of Large Language Models Textcited by 3
  6. 2026'Your AI Text is not Mine': Redefining and Evaluating AI-generated Text Detection under Realistic Assumptionscited by 3
  7. 2024OffensiveLang: A Community Based Implicit Offensive Language Datasetcited by 2
  8. 2024MUGC: Machine Generated versus User Generated Content Detectioncited by 2
  9. 2024Large Language Models are Good Attackers: Efficient and Stealthy Textual Backdoor Attackscited by 2
  10. 2024An Evaluation of Explanation Methods for Black-Box Detectors of Machine-Generated Textcited by 2
  11. 2025IPAD: Inverse Prompt for AI Detection - A Robust and Interpretable LLM-Generated Text Detectorcited by 2
  12. 2026TSM-Bench: Detecting LLM-Generated Text in Real-World Wikipedia Editing Practicescited by 2
  13. 2023Deep dive into language traits of AI-generated Abstractscited by 1
  14. 2023AI Content Self-Detection for Transformer-based Large Language Modelscited by 1
  15. 2024Unmasking the Imposters: How Censorship and Domain Adaptation Affect the Detection of Machine-Generated Tweetscited by 1
  16. 2026MAGA-Bench: Machine-Augment-Generated Text via Alignment Detection Benchmarkcited by 1
  17. 2026DetectZoo: A Unified Toolkit for AI-Generated Content Detection Across Text, Audio, and Image Modalitiescited by 1
  18. 2024Vietnamese AI Generated Text Detectioncited by 0
  19. 2024SMLT-MUGC: Small, Medium, and Large Texts -- Machine versus User-Generated Content Detection and Comparisoncited by 0
  20. 2025Datum-wise Transformer for Synthetic Tabular Data Detection in the Wildcited by 0
  21. 2025Measuring Human Involvement in AI-Generated Text: A Case Study on Academic Writingcited by 0
  22. 2025Stylometry recognizes human and LLM-generated texts in short samplescited by 0
  23. 2025StylOch at PAN: Gradient-Boosted Trees with Frequency-Based Stylometric Featurescited by 0
  24. 2025Span-level Detection of AI-generated Scientific Text via Contrastive Learning and Structural Calibrationcited by 0
  25. 2026Explaining Generalization of AI-Generated Text Detectors Through Linguistic Analysiscited by 0
  26. 2026Can We Trust LLM Detectors?cited by 0
  27. 2026Science or Slop?: Benchmarking and Mitigating Scientific Slop in AI-Generated Paperscited by 0