mlsanityData to 7 Oct 2026

GPT-Sentinel: Distinguishing Human and ChatGPT Generated Content

arXiv 2305.07969 ↗First posted 13 May 2023cs.CLcited by 40

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Abstract (arXiv)

This paper presents a novel approach for detecting ChatGPT-generated vs. human-written text using language models. To this end, we first collected and released a pre-processed dataset named OpenGPTText, which consists of rephrased content generated using ChatGPT. We then designed, implemented, and trained two different models for text classification, using Robustly Optimized BERT Pretraining Approach (RoBERTa) and Text-to-Text Transfer Transformer (T5), respectively. Our models achieved remarkable results, with an accuracy of over 97% on the test dataset, as evaluated through various metrics. Furthermore, we conducted an interpretability study to showcase our model's ability to extract and differentiate key features between human-written and ChatGPT-generated text. Our findings provide important insights into the effective use of language models to detect generated text.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). Builds on 13 of its 34 references that are in the map. First posted on arXiv 13 May 2023.

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13 of 34 references.

References · 13

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  5. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  6. 2017Axiomatic Attribution for Deep Networkscited by 3,350
  7. 2017Decoupled Weight Decay Regularizationcited by 1,722
  8. 2019ELI5: Long Form Question Answeringcited by 567
  9. 2019Defending Against Neural Fake Newscited by 553
  10. 2019Release Strategies and the Social Impacts of Language Modelscited by 505
  11. 2019GLTR: Statistical Detection and Visualization of Generated Textcited by 490
  12. 2019Automatic Detection of Generated Text is Easiest when Humans are Fooledcited by 260
1 more
  1. 2020Automatic Detection of Machine Generated Text: A Critical Surveycited by 160

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 24; 2025: 7; 2026: 2.

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  1. 2024Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviewscited by 160
  2. 2023DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Textcited by 127
  3. 2024Mapping the Increasing Use of LLMs in Scientific Paperscited by 112
  4. 2023A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directionscited by 101
  5. 2024Detecting Multimedia Generated by Large AI Models: A Surveycited by 73
  6. 2023A Survey on Detection of LLMs-Generated Contentcited by 70
  7. 2024DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learningcited by 52
  8. 2024TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identificationcited by 33
  9. 2023Towards Possibilities & Impossibilities of AI-generated Text Detection: A Surveycited by 28
  10. 2024Between Lines of Code: Unraveling the Distinct Patterns of Machine and Human Programmerscited by 27
  11. 2024Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScorecited by 27
  12. 2025RepreGuard: Detecting LLM-Generated Text by Revealing Hidden Representation Patternscited by 24
28 more
  1. 2024Detecting AI-Generated Text: Factors Influencing Detectability with Current Methodscited by 23
  2. 2024Permute-and-Flip: An optimally stable and watermarkable decoder for LLMscited by 17
  3. 2025Improving Your Model Ranking on Chatbot Arena by Vote Riggingcited by 16
  4. 2023On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlookcited by 15
  5. 2024Zero-Shot Detection of LLM-Generated Text using Token Cohesivenesscited by 13
  6. 2024DALD: Improving Logits-based Detector without Logits from Black-box LLMscited by 12
  7. 2025DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured Hierarchical Representation Learningcited by 12
  8. 2024Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Bettercited by 11
  9. 2023On the Generalization of Training-based ChatGPT Detection Methodscited by 9
  10. 2024'Quis custodiet ipsos custodes?' Who will watch the watchmen? On Detecting AI-generated peer-reviewscited by 8
  11. 2025Human Texts Are Outliers: Detecting LLM-generated Texts via Out-of-distribution Detectioncited by 8
  12. 2024Humanizing the Machine: Proxy Attacks to Mislead LLM Detectorscited by 6
  13. 2024Deciphering Textual Authenticity: A Generalized Strategy through the Lens of Large Language Semantics for Detecting Human vs. Machine-Generated Textcited by 5
  14. 2024Survey on Plagiarism Detection in Large Language Models: The Impact of ChatGPT and Gemini on Academic Integritycited by 5
  15. 2024Using Machine Learning to Distinguish Human-written from Machine-generated Creative Fictioncited by 4
  16. 2025Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applicationscited by 4
  17. 2024Generative Models are Self-Watermarked: Declaring Model Authentication through Re-Generationcited by 3
  18. 2024HULLMI: Human vs LLM identification with explainabilitycited by 3
  19. 2024OffensiveLang: A Community Based Implicit Offensive Language Datasetcited by 2
  20. 2023Large Language Models for Conducting Advanced Text Analytics Information Systems Researchcited by 1
  21. 2024Investigating the Influence of Prompt-Specific Shortcuts in AI Generated Text Detectioncited by 1
  22. 2024Discourse Features Enhance Detection of Document-Level Machine-Generated Contentcited by 1
  23. 2025A Practical Synthesis of Detecting AI-Generated Textual, Visual, and Audio Contentcited by 1
  24. 2026Different Time, Different Language: Revisiting the Bias Against Non-Native Speakers in GPT Detectorscited by 1
  25. 2024TextMachina: Seamless Generation of Machine-Generated Text Datasetscited by 0
  26. 2024Who Writes the Review, Human or AI?cited by 0
  27. 2025Measuring Human Involvement in AI-Generated Text: A Case Study on Academic Writingcited by 0
  28. 2026DeBERTa-Sentinel: Toward Transparent and Trustworthy Detection of AI-Generated Textcited by 0