arXiv:2608.30502v1 Announce Type: new
Abstract: Machine learning systems are increasingly corrected while they run, and the decision of when to intervene is increasingly delegated to statistical moni...
By Weijia Han, Lisha Qu
arXiv:2504. 19952v2 Announce Type: replace-cross Abstract: We present two general lower bounds for stopping times of sequential tests between arbitrary composite nulls $\mathcal P$ and alternatives $\mathcal Q$.
By Shubhada Agrawal, Ashwin Ram, Aaditya Ramdas
arXiv:2602. 13848v2 Announce Type: replace Abstract: We propose a sequential test for detecting arbitrary distribution shifts that allows conformal test martingales (CTMs) to work under a fixed, reference-conditional setting.
By Shalev Shaer, Yarin Bar, Drew Prinster, Yaniv Romano
arXiv:2606. 30338v1 Announce Type: new Abstract: External evaluations are becoming increasingly central to the governance of AI systems.
By Ioannis Pitsiorlas, Martha V. Sourla, Marios Kountouris
arXiv:2603. 17925v2 Announce Type: replace-cross Abstract: We consider a variant of sequential testing by betting where, at each time step, the statistician is presented with multiple data sources (arms) and obtains data by choosing one of the arms.
By Ricardo J. Sandoval, Ian Waudby-Smith, Michael I. Jordan
arXiv:2609.37841v1 Announce Type: new
Abstract: Masked generative models offer parallel token prediction, but accurate parallel sampling must account for dependencies among tokens. When dependencies...
By Ryotaro Kawata, Satoshi Hayakawa, Taiji Suzuki