Cover Image

Calibrated? Not for Everyone: How Sexual Orientation and Religious Markers Distort LLM Accuracy and Confidence in Medical QA

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Testoni, Alberto, Calixto, Iacer
Format:	Preprint
Published:	2026
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mind the Gap: Benchmarking LLM Uncertainty and Calibration with Specialty-Aware Clinical QA and Reasoning-Based Behavioural Features
by: Testoni, Alberto, et al.
Published: (2025)

AnyMatch -- Efficient Zero-Shot Entity Matching with a Small Language Model
by: Zhang, Zeyu, et al.
Published: (2024)

Asking the Right Question at the Right Time: Human and Model Uncertainty Guidance to Ask Clarification Questions
by: Testoni, Alberto, et al.
Published: (2024)

Enhancing Marker Scoring Accuracy through Ordinal Confidence Modelling in Educational Assessments
by: Chakravarty, Abhirup, et al.
Published: (2025)

Agentic Confidence Calibration
by: Zhang, Jiaxin, et al.
Published: (2026)

LLM for Everyone: Representing the Underrepresented in Large Language Models
by: Cahyawijaya, Samuel
Published: (2024)

This Treatment Works, Right? Evaluating LLM Sensitivity to Patient Question Framing in Medical QA
by: Yun, Hye Sun, et al.
Published: (2026)

Evaluating Prompt Engineering Techniques for Accuracy and Confidence Elicitation in Medical LLMs
by: Naderi, Nariman, et al.
Published: (2025)

Differentially Private De-identification of Dutch Clinical Notes: A Comparative Evaluation
by: Miranda, Michele, et al.
Published: (2026)

Calibrating Verbalized Confidence with Self-Generated Distractors
by: Wang, Victor, et al.
Published: (2025)

Fact-Level Confidence Calibration and Self-Correction
by: Yuan, Yige, et al.
Published: (2024)

Double-Calibration: Towards Reliable LLMs via Calibrating Knowledge and Reasoning Confidence
by: Lu, Yuyin, et al.
Published: (2026)

PrinciplismQA: A Philosophy-Grounded Approach to Assessing LLM-Human Clinical Medical Ethics Alignment
by: Hong, Chang, et al.
Published: (2025)

How Confident Is the First Token? An Uncertainty-Calibrated Prompt Optimization Framework for Large Language Model Classification and Understanding
by: Chen, Wei, et al.
Published: (2026)

Self-Anchoring Calibration Drift in Large Language Models: How Multi-Turn Conversations Reshape Model Confidence
by: Harshavardhan
Published: (2026)

Don't Buy it! Reassessing the Ad Understanding Abilities of Contrastive Multimodal Models
by: Bavaresco, A., et al.
Published: (2024)

DeCode: Decoupling Content and Delivery for Medical QA
by: Ko, Po-Jen, et al.
Published: (2026)

Don't Think Twice! Over-Reasoning Impairs Confidence Calibration
by: Lacombe, Romain, et al.
Published: (2025)

A Survey of Confidence Estimation and Calibration in Large Language Models
by: Geng, Jiahui, et al.
Published: (2023)

How LLMs Distort Our Written Language
by: Abdulhai, Marwa, et al.
Published: (2026)

Confidence and Calibration of Activation Oracles for Reliable Interpretation of Language Model Internals
by: Torrielli, Federico, et al.
Published: (2026)

LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language Models
by: Stengel-Eskin, Elias, et al.
Published: (2024)

MedExQA: Medical Question Answering Benchmark with Multiple Explanations
by: Kim, Yunsoo, et al.
Published: (2024)

Improving LLM Reliability with RAG in Religious Question-Answering: MufassirQAS
by: Alan, Ahmet Yusuf, et al.
Published: (2024)

The Dunning-Kruger Effect in Large Language Models: An Empirical Study of Confidence Calibration
by: Ghosh, Sudipta, et al.
Published: (2026)

Confidence-Calibrated Small-Large Language Model Collaboration for Cost-Efficient Reasoning
by: Zhang, Chuang, et al.
Published: (2026)

Improving the Calibration of Confidence Scores in Text Generation Using the Output Distribution's Characteristics
by: Flores, Lorenzo Jaime Yu, et al.
Published: (2025)

Mind the Confidence Gap: Overconfidence, Calibration, and Distractor Effects in Large Language Models
by: Chhikara, Prateek
Published: (2025)

From Confidence to Collapse in LLM Factual Robustness
by: Fastowski, Alina, et al.
Published: (2025)

PassiveQA: A Three-Action Framework for Epistemically Calibrated Question Answering via Supervised Finetuning
by: Baidya, Madhav S
Published: (2026)

Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA
by: Roy, Nirmal, et al.
Published: (2024)

LLM4Causal: Democratized Causal Tools for Everyone via Large Language Model
by: Jiang, Haitao, et al.
Published: (2023)

Sacred or Synthetic? Evaluating LLM Reliability and Abstention for Religious Questions
by: Atif, Farah, et al.
Published: (2025)

Beyond Accuracy: The Role of Calibration in Self-Improving Large Language Models
by: Huang, Liangjie, et al.
Published: (2025)

LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models
by: Yang, Hang, et al.
Published: (2024)

LLM as a Broken Telephone: Iterative Generation Distorts Information
by: Mohamed, Amr, et al.
Published: (2025)

Multi-LLM QA with Embodied Exploration
by: Patel, Bhrij, et al.
Published: (2024)

No Reader Left Behind: Multi-Agent Summaries Everyone Can Understand
by: Jung, Jimin, et al.
Published: (2026)

PACR: Progressively Ascending Confidence Reward for LLM Reasoning
by: Yoon, Eunseop, et al.
Published: (2025)

Confidence Estimation for LLM-Based Dialogue State Tracking
by: Sun, Yi-Jyun, et al.
Published: (2024)