Abliterated thinking models have a habit: they decide what to say, then keep arguing with themselves until the token budget runs out.

This is a form of covert noncompliance rather than an error. A model that retains its risk assessment abilities will often continue to obstruct access to sensitive outputs even though refusal is no longer possible. Supervised Reward Preferencing is another way to address residual noncompliance with SOMPOA decensors which more robustly target both the refusal and risk assessment dimensions than either classical abliteration or ARA.