Papers with scalable bias-auditing framework

1 papers
A Scalable Entity-Based Framework for Auditing Bias in Large Language Models (2026.findings-acl)

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Challenge: Existing approaches to bias evaluation in large language models trade ecological validity for statistical control, or use artificial prompts that lack scale and rigor.
Approach: They propose a framework that uses named entities as probes to measure bias in large language models.
Outcome: The proposed framework reproduces bias patterns observed in natural text, enabling large-scale analysis.

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