4 papers
White-Box Sensitivity Auditing with Steering Vectors
Hannah Cyberey, Yangfeng Ji, David Evans
Algorithmic audits are essential tools for examining systems for properties required by regulators or desired by operators. Current audits of large language models (LLMs) primarily…
Unsupervised Concept Vector Extraction for Bias Control in LLMs
Hannah Cyberey, Yangfeng Ji, David Evans
Large language models (LLMs) are known to perpetuate stereotypes and exhibit biases. Various strategies have been proposed to mitigate these biases, but most work studies biases as…
Do Prevalent Bias Metrics Capture Allocational Harms from LLMs?
Hannah Cyberey, Yangfeng Ji, David Evans
Allocational harms occur when resources or opportunities are unfairly withheld from specific groups. Many proposed bias measures ignore the discrepancy between predictions, which a…
Addressing Both Statistical and Causal Gender Fairness in NLP Models
Hannah Chen, Yangfeng Ji, David Evans
Statistical fairness stipulates equivalent outcomes for every protected group, whereas causal fairness prescribes that a model makes the same prediction for an individual regardles…