Papers with mitigation measures

1 papers
Bias Analysis and Mitigation through Protected Attribute Detection and Regard Classification (2025.findings-emnlp)

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Challenge: Large language models acquire general knowledge from pretraining but pretraining data contain undesirable social biases which can be perpetuated or even amplified by LLMs.
Approach: They propose an efficient yet effective annotation pipeline to investigate social biases in pretraining data.
Outcome: The proposed pipeline investigates social biases in the pretraining corpus using protected attribute detection and regard classification.

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