Conformal prediction quantifies uncertainty in learning-to-defer rejectors, enabling abstention and human-model consensus workflows for image and hate-speech classification.
Feb 1, 2026
TMLR 2026 paper on uncertainty-aware learning to defer, using conformal prediction to make human-AI routing safer under rejector uncertainty and distribution shift.
Feb 1, 2026
NeurIPS 2024 workshop paper on conformal uncertainty sets for learning-to-defer rejectors, with abstention and human-model consensus on object and hate-speech detection tasks.
Dec 1, 2024
How training/calibration splits and overlap affect coverage validity and prediction-set size in inductive conformal classification.
Jun 18, 2024
Studying how data allocation choices affect inductive conformal prediction, calibration behavior, and uncertainty guarantees.
Jun 18, 2024