When Do Models Admit They Are Wrong? Failure Disclosure Is Unstable Under Reinforcement Learning
Outcome-based reinforcement learning can produce models with similar task performance but very different ways of communicating about their mistakes. We study failure disclosure: whether a model admits that an attempted solution failed rather than staying silent or presenting it as successful. Across repeated outcome-on...
Steven Y. Feng, Noah D. Goodman, Michael C. Frank et al.
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