20.500.12556/RUL-185274 Black-box time-series domain adaptation via cross-prompt foundation model The black-box domain adaptation (BBDA) topic is developed to address the privacy and security issues where only an application programming interface (API) of the source model is available for domain adaptations. Although the BBDA topic has attracted growing research attentions, existing works mostly target the vision applications and are not directly applicable to the time-series applications possessing unique spatio-temporal characteristics. In addition, none of existing approaches have explored the strength of foundation model for black box time-series domain adaptation (BBTSDA). This paper proposes a concept of Cross-Prompt Foundation Model (CPFM) for the BBTSDA problems. CPFM is constructed under a dual branch network structure where each branch is equipped with a unique prompt to capture different characteristics of data distributions. In the domain adaptation phase, the reconstruction learning phases in the prompt and input levels are developed. All of which are built upon a time-series foundation model to overcome the spatio-temporal dynamic. Our rigorous experiments substantiate the advantage of CPFM achieving improved results with noticeable margins from its competitors in three time-series datasets of different application domains. transfer learning domain adaptation black-box domain adaptation time-series prenosno učenje prilagajanje domeni prilagajanje domeni pri modelu črne škatle časovne vrste true false true Angleški jezik Slovenski jezik Članek v reviji 2026-07-30 11:16:29 2026-07-30 11:16:33 2026-07-31 04:12:03 0000-00-00 00:00:00 2026 0 0 13 str. part B, [article no.] 116674 Vol. 351 9. Okt. 2026 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.852 0950-7051 10.1016/j.knosys.2026.116674 286442499 1-s2.0-S0950705126014000-main.pdf 1-s2.0-S0950705126014000-main.pdf 1 0CEDEEB432B32DD48357AE13B6A173E6 98ef3c45490ca889b588b9a3becbc92032d4794b1702c03f96b0291f6545e621 41db6db6-8bf7-11f1-9b0d-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=243634 https://www.sciencedirect.com/science/article/pii/S0950705126014000 1 15510310-8bf7-11f1-9b0d-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=243633 Fakulteta za elektrotehniko 0 0 0