1 citations · 2 across the 2 of their papers we have counts for
7 papers
How Robust Is Homogeneity Bias in LLMs? Evidence Across Models, Decoding Settings, and Identity Signals
Messi H. J. Lee
Large language models (LLMs) reproduce homogeneity bias -- the tendency to portray marginalized groups as more internally similar than dominant groups -- but whether this bias gene…
Token-Level Entropy Reveals Demographic Disparities in Large Language Models
Messi H. J. Lee
A name alone measurably reshapes a language model's next-token distribution before a single token is sampled. We measure full-vocabulary Shannon entropy of the next-token distribut…
Language model agents show in-group trust bias invisible to standard behavioural audits
Messi H. J. Lee
Language-model agents are moving from single-user assistants into persistent networks that build trust and reputation with one another, and the same models increasingly control phy…
Implicit Bias-Like Patterns in Reasoning Models
Messi H. J. Lee, Calvin K. Lai
Implicit biases refer to automatic mental processes that shape perceptions, judgments, and behaviors. Previous research on "implicit bias" in LLMs focused primarily on outputs rath…
Vision-Language Models Generate More Homogeneous Stories for Phenotypically Black Individuals
Messi H. J. Lee, Soyeon Jeon
Vision-Language Models (VLMs) extend Large Language Models' capabilities by integrating image processing, but concerns persist about their potential to reproduce and amplify human…
Visual Cues of Gender and Race are Associated with Stereotyping in Vision-Language Models
Messi H. J. Lee, Soyeon Jeon, Jacob M. Montgomery +1
Current research on bias in Vision Language Models (VLMs) has important limitations: it is focused exclusively on trait associations while ignoring other forms of stereotyping, it…