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Adaptation Interfaces for In-Context Tabular Foundation Models in Time-to-Event Prediction
A new arXiv paper examines how tabular foundation models, which perform well on standard classification and regression tasks, can be adapted to time-to-event (survival) prediction. The authors propose adaptation interfaces to address the difficulty that censored outcomes pose for in-context learning. The work is listed under both machine learning and AI categories on arXiv.