3 papers
cs.CL2026
When Models Refuse: Political Steerability and Feature Richness as Measures of Ideological Depth
Shariar Kabir
Large language models (LLMs) sometimes refuse to follow benign instructions, such as declining to argue a political position or adopt a stated persona, and such refusals are common…
cs.CL2026
PReSS: An Automated Black-Box Framework for Evaluating Political Stance Stability in LLMs
Shariar Kabir, Kevin Esterling, Yue Dong
Existing evaluations of political bias in large language models (LLMs) typically classify outputs as left- or right-leaning. We extend this perspective by examining how ideological…
cs.HC2025
AmarDoctor: An AI-Driven, Multilingual, Voice-Interactive Digital Health Application for Primary Care Triage and Patient Management to Bridge the Digital Health Divide for Bengali Speakers
Nazmun Nahar, Ritesh Harshad Ruparel, Shariar Kabir +3
This study presents AmarDoctor, a multilingual voice-interactive digital health app designed to provide comprehensive patient triage and AI-driven clinical decision support for Ben…