Dialect vs Demographics: Quantifying LLM Bias from Implicit Linguistic Signals vs. Explicit User Profiles

ArXi:2604.21152v1 Announce Type: cross As state-of-the-art Large Language Models (LLMs) have become ubiquitous, ensuring equitable performance across diverse graphics is critical. However, it remains unclear whether these disparities arise from the explicitly stated identity itself or from the way identity is signaled. In real-world interactions, users' identity is often conveyed implicitly through a complex combination of various socio-linguistic factors.