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cs.LG2026
Learning Across Heterogeneous Feature Spaces with Group Robustness
Xenia Konti, Arjun Tschand, Chuan Hong +2
In clinical applications, patients undergo different combinations of tests, and machine learning models must therefore ensure accurate predictions across heterogeneous feature spac…
cs.CL2026
SIMAX: A Scalable and Interpretable Framework for Multi-Fidelity and Annotated Clinician-Patient Dialogue Simulation
Zhuhan Bao, Rui Yang, Bohao Yang +16
Background. The widespread deployment of ambient digital scribes is driving large-scale capture of clinician-patient dialogues. Human coding of clinical communication data remains…