Reproduce “Two for One: Privileged Learning for Resource-Constrained Screening” on OpenResearch
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About this paper
Lisa Y.W. Tang
The authors train a one-eye retinal model using bilateral teacher features, then deploy the student with only one eye at inference. On ODIR-5K, the privileged student raises left-eye diabetic-retinopathy AUROC from 0.789 to 0.836. The result supports transfer of training-time context, but comes from one held-out test set and does not establish statistical significance or external generalizability.
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