5 citations · 10 across the 6 of their papers we have counts for
Showing 2024 · cs.CLShow all
2 papers · 2 filters
cs.CL2024★ 1 cited
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…
cs.CL2024
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…