arXiv:2606. 04564v1 Announce Type: new Abstract: Tabular foundation models (TFMs) have made rapid progress in standard classification and regression, but time-to-event survival prediction tasks have remained largely untouched.
By Samuel B\"ohm (Institute of Epidemiology and Prevention, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany), Lennart Purucker (Department of Computer Science, University of Freiburg, Freiburg, Germany, PriorLabs, Freiburg, Germany), Frank Hutter (Department of Computer Science, University of Freiburg, Freiburg, Germany, PriorLabs, Freiburg, Germany), Pascal Schlosser (Institute of Epidemiology and Prevention, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, US, CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany)
arXiv:2607. 22268v1 Announce Type: cross Abstract: Remaining useful life (RUL) prediction and failure-mode classification are central tasks in predictive maintenance.
By Hao Yan, Ali Sarabi, Qing Zou, Boyang Xu
The paper explores remaining useful life (RUL) estimation using multimodal large language models (MLLMs) that are grounded through time‑series retrieval. It proposes a framework that retrieves historically similar degradation segments, combines them with the test trajectory into a visual comparison artifact, and processes this via a structured multimodal prompt. Experiments on the FD001 partition of the C‑MAPSS benchmark show that retrieval consistently improves RUL prediction, with greater benefits for larger MLLMs, while also revealing current limitations in practical prognostics and health management (PHM) settings.
By Valeriu Dimidov, Rapha\"el Frank
arXiv:2608. 19218v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are increasingly being explored for domain-specific maintenance and prognostics tasks, raising the question of whether they can effectively support prognostics and health management (PHM).
By Valeriu Dimidov, Rapha\"el Frank
arXiv:2601. 22259v2 Announce Type: replace Abstract: While tabular foundation models have achieved remarkable success in classification and regression, adapting them to model time-to-event outcomes for survival analysis is non-trivial due to right-censoring, where data observations may end before the event of interest occurs.
By Da In Kim, Wei Siang Lai, Kelly W. Zhang