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UC San Diego
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Opportunistic Backdoors (OPBackdoor), in which the backdoor objective is elicited only when the triggered prompt context presents an exploitable opportunity, enabling the model's think to disguise its pursuit through alibi-aligned reasoning that is logical with respect to the triggered prompt context but directly leads to the target response.
On-policy self-distillation can boost diffusion model performance by up to 44% while slashing training time by over 60%.
