7 citations · 9 across the 3 of their papers we have counts for
3 papers
The Impossibility of Fair LLMs
Jacy Anthis, Kristian Lum, Michael Ekstrand +2
The rise of general-purpose artificial intelligence (AI) systems, particularly large language models (LLMs), has raised pressing moral questions about how to reduce bias and ensure…
Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation
Kristian Lum, Jacy Reese Anthis, Kevin Robinson +2
Standard benchmarks of bias and fairness in large language models (LLMs) measure the association between the user attributes stated or implied by a prompt and the LLM's short text…
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
Benjamin Eyre, Elliot Creager, David Madras +2
Designing deep neural network classifiers that perform robustly on distributions differing from the available training data is an active area of machine learning research. However,…