2 citations · 3 across the 5 of their papers we have counts for
3 papers · 1 filter
Overconfidence and Calibration in Medical VQA: Empirical Findings and Hallucination-Aware Mitigation
Ji Young Byun, Young-Jin Park, Jean-Philippe Corbeil +1
As vision-language models (VLMs) are increasingly deployed in clinical decision support, more than accuracy is required: knowing when to trust their predictions is equally critical…
Test-Time-Scaling for Zero-Shot Diagnosis with Visual-Language Reasoning
Ji Young Byun, Young-Jin Park, Navid Azizan +1
As a cornerstone of patient care, clinical decision-making significantly influences patient outcomes and can be enhanced by large language models (LLMs). Although LLMs have demonst…
Uncertainty Quantification in Detection Transformers: Object-Level Calibration and Image-Level Reliability
Young-Jin Park, Carson Sobolewski, Navid Azizan
DETR and its variants have emerged as promising architectures for object detection, offering an end-to-end prediction pipeline. In practice, however, DETRs generate hundreds of pre…