arXiv Machine Learning June 2, 2026 By Sudarshan Sreeram, Young D. Kwon, Cecilia Mascolo

Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation

Read the original on arXiv Machine Learning →

arXiv:2602. 06136v2 Announce Type: replace Abstract: Test-time adaptation (TTA) offers a compelling remedy for machine learning (ML) models that degrade under domain shifts, improving generalisation on-the-fly with only unlabelled samples.

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

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Jul 1

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BP-TTA: Balanced and Prototype-Guided Test-Time Adaptation in Dynamic Scenarios

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Prescriptive Scaling Reveals the Evolution of Language Model Capabilities

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