Papers by Anton Ragni

1 papers
HERB: Measuring Hierarchical Regional Bias in Pre-trained Language Models (2022.findings-aacl)

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Challenge: Existing methods do not examine social groups categorised by geographical information, leaving the region-related biases in pre-trained LMs unexplored.
Approach: They propose a hierarchical regional bias evaluation method to quantify regional bias in pre-trained language models.
Outcome: The proposed method evaluates regional bias with regard to comprehensive topics and measures potential regional bias that can be propagated to downstream tasks.

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