Introduces a culturally grounded bias lexicon for intersectional South Asian stigmas and evaluates its use in measuring and mitigating bias in open-ended multilingual LLM outputs.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CL 2years
2025 2verdicts
UNVERDICTED 2representative citing papers
Across 43,200 simulations with five LLMs and five scenarios, model trust in humans aligns with human-like patterns driven by trustworthiness dimensions and is sometimes biased by age, gender, and religion.
citing papers explorer
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Purdah and Patriarchy: Evaluating and Mitigating South Asian Biases in Open-Ended Multilingual LLM Generations
Introduces a culturally grounded bias lexicon for intersectional South Asian stigmas and evaluates its use in measuring and mitigating bias in open-ended multilingual LLM outputs.
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A closer look at how large language models trust humans: patterns and biases
Across 43,200 simulations with five LLMs and five scenarios, model trust in humans aligns with human-like patterns driven by trustworthiness dimensions and is sometimes biased by age, gender, and religion.