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fairness-evaluation

topic1 events
papersTODAY 04:00 UTC

arXiv Paper Evaluates Intersectional Fairness in Six Large Language Models

A research paper examines how fairness and bias behave in large language models when several sensitive attributes, such as gender and ethnicity, are considered together rather than one at a time. The authors run a systematic evaluation across six LLMs to assess intersectional fairness, a setting relevant to socially sensitive deployments. The work highlights gaps in how current models handle overlapping demographic characteristics.

fairness/bias/evaluation/llm