Theoretical Framework for Test-Time Adaptation Learnability Proposed

A new theoretical framework for studying the learnability of test-time adaptation (TTA) under non-stationary streams has been introduced in a paper on arXiv. The framework addresses the lack of a principled theory that aligns with TTA objectives while capturing evolving distribution shifts and information constraints. Key concepts include (ε,δ)-Recovery Complexity, which measures post-shift time to maintain excess risk below a target level, and (ε,ρ)-TTA Learnability, which assesses long-term reliability. The work proposes a discrete surrogate for non-stationary processes. The paper is authored by researchers and posted on arXiv with ID 2605.28057.