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Adapt or Calibrate? How Local Labels Buy Certified Coverage in Medical VQA
Reza Khanmohammadi, Kundan Thind, Mohammad M. Ghassemi
An answer from a vision-language model (VLM) to a medical image question can be accepted without review only under a threshold bounding the error of accepted answers, and certifyin…
Grounded or Guessing? LVLM Confidence Estimation via Blind-Image Contrastive Ranking
Reza Khanmohammadi, Erfan Miahi, Simerjot Kaur +4
Large vision-language models (LVLMs) suffer from visual ungroundedness: they can produce a fluent, confident, and even correct response driven entirely by language priors, with the…
How Reliable are Confidence Estimators for Large Reasoning Models? A Systematic Benchmark on High-Stakes Domains
Reza Khanmohammadi, Erfan Miahi, Simerjot Kaur +4
The miscalibration of Large Reasoning Models (LRMs) undermines their reliability in high-stakes domains, necessitating methods to accurately estimate the confidence of their long-f…
What Language Models Know But Don't Say: Non-Generative Prior Extraction for Generalization
Sara Rezaeimanesh, Kundan Thind, Farzan Siddiqui +1
In domains like medicine and finance, large-scale labeled data is costly and often unavailable, leading to models trained on small datasets that struggle to generalize to real-worl…
Calibrating LLM Confidence by Probing Perturbed Representation Stability
Reza Khanmohammadi, Erfan Miahi, Mehrsa Mardikoraem +5
Miscalibration in Large Language Models (LLMs) undermines their reliability, highlighting the need for accurate confidence estimation. We introduce CCPS (Calibrating LLM Confidence…
Hybrid Student-Teacher Large Language Model Refinement for Cancer Toxicity Symptom Extraction
Reza Khanmohammadi, Ahmed I. Ghanem, Kyle Verdecchia +9
Large Language Models (LLMs) offer significant potential for clinical symptom extraction, but their deployment in healthcare settings is constrained by privacy concerns, computatio…
Iterative Prompt Refinement for Radiation Oncology Symptom Extraction Using Teacher-Student Large Language Models
Reza Khanmohammadi, Ahmed I Ghanem, Kyle Verdecchia +7
This study introduces a novel teacher-student architecture utilizing Large Language Models (LLMs) to improve prostate cancer radiotherapy symptom extraction from clinical notes. Mi…
An Introduction to Natural Language Processing Techniques and Framework for Clinical Implementation in Radiation Oncology
Reza Khanmohammadi, Mohammad M. Ghassemi, Kyle Verdecchia +8
Natural Language Processing (NLP) is a key technique for developing Medical Artificial Intelligence (AI) systems that leverage Electronic Health Record (EHR) data to build diagnost…