mlsanityData to 7 Oct 2026

Release Strategies and the Social Impacts of Language Models

arXiv 1908.09203 ↗First posted 24 Aug 2019cs.CL cs.AI cs.CYcited by 505

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Cited by 43 in LLM safety and security, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Large language models have a range of beneficial uses: they can assist in prose, poetry, and programming; analyze dataset biases; and more. However, their flexibility and generative capabilities also raise misuse concerns. This report discusses OpenAI's work related to the release of its GPT-2 language model. It discusses staged release, which allows time between model releases to conduct risk and benefit analyses as model sizes increased. It also discusses ongoing partnership-based research and provides recommendations for better coordination and responsible publication in AI.

Key facts. Cited by 505 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Aug 2019.

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Citing papers per year: 2020: 1; 2021: 25; 2022: 25; 2023: 124; 2024: 143; 2025: 104; 2026: 83.

505 papers.

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  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  4. 2021Ethical and social risks of harm from Language Modelscited by 957
  5. 2021CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generationcited by 732
  6. 2023DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvaturecited by 705
  7. 2023How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detectioncited by 472
  8. 2023Can AI-Generated Text be Reliably Detected?cited by 372
  9. 2021Unified Pre-training for Program Understanding and Generationcited by 361
  10. 2023The Curse of Recursion: Training on Generated Data Makes Models Forgetcited by 343
  11. 2023Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvaturecited by 278
  12. 2024Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Textcited by 255
38 more
  1. 2023A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPTcited by 221
  2. 2023An Overview of Catastrophic AI Riskscited by 214
  3. 2023DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Textcited by 207
  4. 2021Societal Biases in Language Generation: Progress and Challengescited by 201
  5. 2022BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagecited by 197
  6. 2024ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMscited by 197
  7. 2022SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Controlcited by 191
  8. 2023RADAR: Robust AI-Text Detection via Adversarial Learningcited by 187
  9. 2023Gender bias and stereotypes in Large Language Modelscited by 185
  10. 2023GPT detectors are biased against non-native English writerscited by 175
  11. 2023GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Modelscited by 174
  12. 2023On the Reliability of Watermarks for Large Language Modelscited by 170
  13. 2024Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviewscited by 160
  14. 2024RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectorscited by 157
  15. 2022What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization?cited by 149
  16. 2023Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Modelscited by 144
  17. 2021Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Modelscited by 141
  18. 2021Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implicationscited by 128
  19. 2023DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Textcited by 127
  20. 2023The Science of Detecting LLM-Generated Textscited by 126
  21. 2021TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generationcited by 118
  22. 2023M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detectioncited by 118
  23. 2023Who Wrote this Code? Watermarking for Code Generationcited by 116
  24. 2024Mapping the Increasing Use of LLMs in Scientific Paperscited by 112
  25. 2021A Survey on Data Augmentation for Text Classificationcited by 111
  26. 2023Intrinsic Dimension Estimation for Robust Detection of AI-Generated Textscited by 111
  27. 2025A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deploymentcited by 110
  28. 2023Regulating ChatGPT and other Large Generative AI Modelscited by 102
  29. 2023Frontier AI Regulation: Managing Emerging Risks to Public Safetycited by 95
  30. 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
  31. 2023MGTBench: Benchmarking Machine-Generated Text Detectioncited by 90
  32. 2023Ghostbuster: Detecting Text Ghostwritten by Large Language Modelscited by 90
  33. 2023Stay on topic with Classifier-Free Guidancecited by 90
  34. 2023Identifying and Mitigating the Security Risks of Generative AIcited by 90
  35. 2022The Fallacy of AI Functionalitycited by 88
  36. 2023On the Possibilities of AI-Generated Text Detectioncited by 88
  37. 2021Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speechcited by 81
  38. 2023OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examplescited by 80

50 most cited of 505 All 505 (JSON)