Papers by William Adler
Evaluating Biases in Context-Dependent Sexual and Reproductive Health Questions (2024.findings-emnlp)
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| Challenge: | With the rise in accessibility of chat-based large language models, the public increasingly uses them as question-answering systems for personalized answers. |
| Approach: | They curate a dataset of sexual and reproductive healthcare questions dependent on age, sex, and location attributes and compare their outputs with and without demographic context to determine answer alignment . |
| Outcome: | The results show that young adult female users are favored in the model answers to underspecified questions in the healthcare domain. |
Gender Bias in Decision-Making with Large Language Models: A Study of Relationship Conflicts (2024.findings-emnlp)
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| Challenge: | Large language models acquire beliefs about gender from training data and can therefore generate text with stereotypical gender attitudes. |
| Approach: | They use a decision-making lens to examine gender equity within large language models . they explore relationships through typical and gender-neutral names . |
| Outcome: | The proposed model generation and classification models exhibit stereotypical gender biases . the proposed model generates gender-neutral names, with and without safety enhancements, and egalitarian versus traditional scenarios across topics. |