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Alignment via Training Against Probes Without Losing Monitorability

Lena Libon et al.
arXiv CS · Papers
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Models are usually aligned based on their observed outputs, using demonstrations, preference data, or reward signals. These objectives reward responses that look aligned. More capable models may learn to satisfy them without internalizing the intended behavior, for example by faking compliance durin
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