Papers by Gene Kim

2 papers
Investigating Subtler Biases in LLMs: Ageism, Beauty, Institutional, and Nationality Bias in Generative Models (2024.findings-acl)

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Challenge: Recent advances in language generation models can be used to assist users in a variety of tasks, but there are risks associated with introducing LLM biases into consequential decisions.
Approach: They propose to use a template-generated dataset to measure subtler correlated decisions that LLMs make between social groups and unrelated positive and negative attributes.
Outcome: The proposed model can be used to evaluate progress in more generalized biases and extend the benchmark with minimal human annotation.
“Global is Good, Local is Bad?”: Understanding Brand Bias in LLMs (2024.emnlp-main)

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Challenge: a recent study examined social biases in LLMs but brand bias has received little attention.
Approach: They examine the behavior of LLMs in the market place by analyzing a brand-based dataset . they find a consistent pattern of brand bias in this space .
Outcome: The proposed model favors established global brands while marginalizing local ones . the proposed model could boost local brand preference in LLM outputs in specific contexts .

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