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K. Adhikari

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Jul 2026

Presentation by Virally Infected Cells of Antigenic Proteins Utilized in Natural Killer Cell Antibody-Dependent Cell-mediated Cytotoxicity (ADCC) 2256335

The data indicate that antibodies to the S protein alone are unlikely to support ADCC to coronavirally infected cells, and that depletion of anti-S from antisera from infected persons had negligible effect on ADCC.

Dorothy Hudig, K. Adhikari, Kendra Cook et al. · 0 citations
#machine learning Review Aug 2026

Training-Free Human-in-the-Loop Anomaly Detection via Memory Bank Correction

Anomaly detectors are hardest to deploy exactly where training data is scarcest: a newly commissioned production line has a handful of verified"golden"samples and no machine-learning engineer on the factory floor. We present a training-free human-in-the-loop framework in which a domain expert corrects a PatchCore detector by direct memory bank editing: no retraining, no gradients, no original training data. A false-positive correction inserts the reviewed image's normal patches through a self-calibrating novelty gate admitting only those beyond the median pool-normal nearest-neighbour distance. From a bank built on only ten golden samples, operator corrections close a median 66% of the gap to an uncorrected fully trained bank (mean 80%, raised by three categories that overshoot parity), significantly improving 12 of 15 MVTec AD categories and harming none: ten samples plus corrections outperform hundreds of samples without them. On already-trained banks the headroom is smaller and concentrated where the bank undersamples normal appearance (gated: toothbrush +0.10, metal nut +0.09, zipper +0.05, screw +0.05), and no category except grid is significantly harmed. Evaluation uses a held-out protocol (20 splits per category, Holm-corrected Wilcoxon), because corrected images entering the bank inflate naive evaluation toward AUROC 1.0 by memorisation. Passive and active querying are statistically indistinguishable; a matched-label-budget control attributes gains to deployment-time label production at 43% of exhaustive-review cost; a defect-memory extension fails decisively. Feedback is simulated from ground truth; live expert trials, where mislabelling is costliest on small banks, remain future work.

Ayusha Abbas, Saram Abbas, K. Adhikari · 0 citations

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