3 papers
cs.CL2025
AAVENUE: Detecting LLM Biases on NLU Tasks in AAVE via a Novel Benchmark
Abhay Gupta, Philip Meng, Ece Yurtseven +2
Detecting biases in natural language understanding (NLU) for African American Vernacular English (AAVE) is crucial to developing inclusive natural language processing (NLP) systems…
astro-ph.CO2025
A Model-Independent Radio Telescope Dark Matter Search in the L and S Bands
Aya Keller, Nicole Wolff, Karl van Bibber
Ultralight bosonic dark matter in its most general form can be detected through its decay or annihilation to a quasimonochromatic radio line. Assuming only that this line is consis…
cs.CL2024
DiversityMedQA: Assessing Demographic Biases in Medical Diagnosis using Large Language Models
Rajat Rawat, Hudson McBride, Dhiyaan Nirmal +5
As large language models (LLMs) gain traction in healthcare, concerns about their susceptibility to demographic biases are growing. We introduce {DiversityMedQA}, a novel benchmark…