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About this paper
Tianyi Lorena Yan, John Hewitt
The authors test whether reward misspecification makes chain-of-thought monitoring harder across three tasks. They train models with aligned or misspecified rewards, then use logged rollouts to teach reward descriptions. This raises average monitorability scores, but does not reliably prevent hacking: average hack rate falls from 0.87 to 0.79, with outcomes varying across model-task pairs.
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