mlsanityData to 7 Oct 2026

RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text

arXiv 2010.03070 ↗First posted 6 Oct 2020cs.CL cs.AI cs.HCcited by 36

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Abstract (arXiv)

In recent years, large neural networks for natural language generation (NLG) have made leaps and bounds in their ability to generate fluent text. However, the tasks of evaluating quality differences between NLG systems and understanding how humans perceive the generated text remain both crucial and difficult. In this system demonstration, we present Real or Fake Text (RoFT), a website that tackles both of these challenges by inviting users to try their hand at detecting machine-generated text in a variety of domains. We introduce a novel evaluation task based on detecting the boundary at which a text passage that starts off human-written transitions to being machine-generated. We show preliminary results of using RoFT to evaluate detection of machine-generated news articles.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Oct 2020.

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Citing papers per year: 2021: 4; 2022: 9; 2023: 9; 2024: 4; 2025: 9; 2026: 1.

36 papers.

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  1. 2021All That's 'Human' Is Not Gold: Evaluating Human Evaluation of Generated Textcited by 287
  2. 2021Hurdles to Progress in Long-form Question Answeringcited by 166
  3. 2024RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectorscited by 157
  4. 2023The Science of Detecting LLM-Generated Textscited by 126
  5. 2023A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directionscited by 101
  6. 2021Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Textcited by 89
  7. 2022Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Surveycited by 80
  8. 2022Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methodscited by 75
  9. 2022Real or Fake Text?: Investigating Human Ability to Detect Boundaries Between Human-Written and Machine-Generated Textcited by 63
  10. 2023Contrasting Linguistic Patterns in Human and LLM-Generated News Textcited by 62
  11. 2024M4GT-Bench: Evaluation Benchmark for Black-Box Machine-Generated Text Detectioncited by 43
  12. 2022Attribution and Obfuscation of Neural Text Authorship: A Data Mining Perspectivecited by 40
24 more
  1. 2024Few-Shot Detection of Machine-Generated Text using Style Representationscited by 40
  2. 2025People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated textcited by 39
  3. 2022Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russiancited by 29
  4. 2021Unsupervised and Distributional Detection of Machine-Generated Textcited by 23
  5. 2023AI vs. Human -- Differentiation Analysis of Scientific Content Generationcited by 21
  6. 2023Does Human Collaboration Enhance the Accuracy of Identifying LLM-Generated Deepfake Texts?cited by 21
  7. 2023Creating a Large Language Model of a Philosophercited by 20
  8. 2023AI-generated text boundary detection with RoFTcited by 20
  9. 2022A Benchmark Corpus for the Detection of Automatically Generated Text in Academic Publicationscited by 18
  10. 2023Detecting ChatGPT: A Survey of the State of Detecting ChatGPT-Generated Textcited by 10
  11. 2025GenAI Content Detection Task 3: Cross-Domain Machine-Generated Text Detection Challengecited by 7
  12. 2025DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attributioncited by 5
  13. 2022DIALOG-22 RuATD Generated Text Detectioncited by 3
  14. 2024Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detectioncited by 3
  15. 2025Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systemscited by 3
  16. 2025Fine-Grained Detection of AI-Generated Text Using Sentence-Level Segmentationcited by 3
  17. 2022Repro: An Open-Source Library for Improving the Reproducibility and Usability of Publicly Available Research Codecited by 2
  18. 2022Synthetic Text Detection: Systemic Literature Reviewcited by 2
  19. 2023How well can machine-generated texts be identified and can language models be trained to avoid identification?cited by 1
  20. 2025Detection Avoidance Techniques for Large Language Modelscited by 1
  21. 2025Domain Gating Ensemble Networks for AI-Generated Text Detectioncited by 0
  22. 2025Mixture of Detectors: A Compact View of Machine-Generated Text Detectioncited by 0
  23. 2025COIG-Writer: A High-Quality Dataset for Chinese Creative Writing with Thought Processescited by 0
  24. 2026LA-CPD: Local-Evidence-Aware Change-Point Detection for Human-LLM Authorship Segmentationcited by 0