Muskaan Chopra has been awarded the Grace Hopper Award by the Institute of Computer Science at the University of Bonn, recognizing her academic excellence and research on reliable machine translation. She will continue with our group as a PhD candidate.
Instruction-tuned and fine-tuned LLMs can substantially improve critical error detection in machine translation, making them useful safeguards for safer multilingual information access.
A survey of deep learning for diabetic retinopathy screening (2016–2025), spanning 50+ studies and 20+ datasets. The key takeaway: strong benchmark scores don't equal clinical readiness: the field needs reproducible code, external validation, calibration, and per-patient evaluation.
RL fine-tuning (GRPO) lifted our chest X-ray model's score 23% on one benchmark but dropped it 19% on another: it learned to predict dataset-specific labels, not to read X-rays. The same pattern appears at 50x the budget, so the problem is the recipe, not the resources. Carefully curated SFT generalized better across institutions.