Bhanu Prakash Vangala

A model trained solely on file metadata—with zero medical imaging data—hits 0.992 balanced accuracy on a flagship pediatric x-ray benchmark, proving that evaluation artifacts and pipeline choices dominate architectural gains.

Standard pooled conformal prediction hides critical safety failures in multilingual models, allowing individual African languages to silently drop to 77.5% reliability despite satisfying a global 90% guarantee.

Cross-lingual data pooling acts as a powerful low-resource jumpstart—boosting macro-F1 by up to 0.43 at 25 labels—but predictably degenerates into negative transfer once local annotations surpass 800 examples.