Is DPO bidirectionally shallow edit?
As part of the BlueDot AI Safety project programme, I studied the bidirectionality of Direct Preference Optimization (DPO), a preference-optimization method used to align models toward desired behaviour. The motivation came from discussions in the Technical Safety course, which drew me toward alignment and interpretability. A paper by Lee et al. (arXiv:2401.01967) studies whether DPO’s edits are “shallow” when used to remove toxicity, and shows that DPO doesn’t erase the toxic capability — it learns a distributed offset that bypasses it, leaving the behaviour reactivatable. ...