AI RESEARCH
Technical note on Sequential Test-Time Adaptation via Martingale-Driven Fisher Prompting
arXiv CS.LG
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ArXi:2510.03839v2 Announce Type: replace We present a theoretical framework for M-FISHER, a method for sequential distribution shift detection and stable adaptation in streaming data. For detection, we construct an exponential martingale from non-conformity scores and apply Ville's inequality to obtain time-uniform guarantees on false alarm control, ensuring statistical validity at any stopping time.