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Release Strategies and the Social Impacts of Language Models

About

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.

Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, Gretchen Krueger, Jong Wook Kim, Sarah Kreps, Miles McCain, Alex Newhouse, Jason Blazakis, Kris McGuffie, Jasmine Wang• 2019

Related benchmarks

TaskDatasetResultRank
Machine-generated text detectionMGT benchmark Essay
AUROC98.3
129
LGT DetectionFast-DetectGPT PubMed (test)
AUROC0.884
96
LGT DetectionFast-DetectGPT XSum (test)
AUROC97.9
96
LGT DetectionXSum Fast-DetectGPT benchmark
AUROC97.9
54
LGT DetectionWritingPrompts-small Fast-DetectGPT benchmark
AUROC97.6
54
LGT DetectionWritingPrompts small Fast-DetectGPT benchmark (test)
AUROC97.6
54
LGT DetectionPubMed Fast-DetectGPT benchmark
AUROC0.878
54
LGT DetectionMGTBench WritingPrompts
AUROC97.3
45
Machine-generated text detectionMGT benchmark Reuters
AUROC99.9
45
LGT DetectionFast-DetectGPT WP-s (test)
AUROC98.1
42
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