arXiv Machine Learning August 11, 2026 By Yiyao Yang

From Uncertainty to Failure Attribution: Self-Diagnosing Models for Failure Attribution under Distribution Shift

Read the original on arXiv Machine Learning →

arXiv:2608. 07953v1 Announce Type: new Abstract: Distribution shift poses a significant challenge to the robustness of machine learning models, but the current solutions only aim to detect out-of-distribution (OOD) samples and predict uncertainty levels.

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

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