arXiv Machine Learning June 17, 2026 By Salimeh Sekeh, Xin Zhang

Theoretical Grounding of Out-Of-Distribution Detection With Reinforcement Learning Optimizer

Read the original on arXiv Machine Learning →

arXiv:2606. 17477v1 Announce Type: cross Abstract: Out-of-distribution (OOD) detection in dynamic open-world environments requires a model to continually adapt to evolving data distributions while generalizing to covariate-shifted inputs and rejecting semantic-shifted OOD examples.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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