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Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

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Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2715606750

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

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Full title

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

Author / Creator

Ganguli, Deep , Lovitt, Liane , Jackson Kernion , Askell, Amanda , Bai, Yuntao , Kadavath, Saurav , Mann, Ben , Perez, Ethan , Schiefer, Nicholas , Ndousse, Kamal , Jones, Andy , Bowman, Sam , Chen, Anna , Conerly, Tom , DasSarma, Nova , Drain, Dawn , Nelson Elhage , El-Showk, Sheer , t, Stanislav , Hatfield-Dodds, Zac , Henighan, Tom , Hernandez, Danny , Hume, Tristan , Jacobson, Josh , Johnston, Scott , Kravec, Shauna , Olsson, Catherine , Ringer, Sam , Tran-Johnson, Eli , Amodei, Dario , Brown, Tom , Nicholas, Joseph , McCandlish, Sam , Olah, Chris , Kaplan, Jared and Clark, Jack

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2022-11

Language

English

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Articles

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

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Subjects and topics

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Scope and Contents

Contents

We describe our early efforts to red team language models in order to simultaneously discover, measure, and attempt to reduce their potentially harmful outputs. We make three main contributions. First, we investigate scaling behaviors for red teaming across 3 model sizes (2.7B, 13B, and 52B parameters) and 4 model types: a plain language model (LM)...

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Full title

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

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Record Identifier

TN_cdi_proquest_journals_2715606750

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2715606750

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E-ISSN

2331-8422

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