Mitigating the Likelihood Paradox in Flow-based OOD Detection: An Entropic Perspective.

arXiv:2602.09581v3 Announce Type: replace-cross Abstract: Deep generative models that can tractably compute input likelihoods, including normalizing flows, often assign unexpectedly high likelihoods to out-of-distribution (OOD) inputs. We mitigate this paradox