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20242026
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cs.CL2026

Calibrated Triage, Not Autonomy: Confidence Estimation for Medical Vision-Language Models

Reza Khanmohammadi, Kundan Thind, Mohammad M. Ghassemi

A vision-language model can answer a question about a chest radiograph or a pathology slide fluently and confidently while barely using the image, relying instead on language prior…

cs.CL2026

Grounded or Guessing? LVLM Confidence Estimation via Blind-Image Contrastive Ranking

Reza Khanmohammadi, Erfan Miahi, Simerjot Kaur +4

Large vision-language models suffer from visual ungroundedness: they can produce a fluent, confident, and even correct response driven entirely by language priors, with the image c…

cs.CL2026

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…

cs.CL2025

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…

cs.CL2024

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…