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LLMs show transformed, not transferred, bias across English and Swahili

By PulseAugur Editorial · [1 sources] ·

A new research paper analyzes the cross-lingual bias present in large language models like GPT-5.2 and Gemini 2.5 Flash. By submitting symmetric English and Swahili prompt pairs, the study found that biases transform rather than transfer between languages, with significant shifts in stereotype rates and refusal behaviors. The research highlights that English-centric bias audits are insufficient for ensuring equitable performance in multilingual LLM deployments. AI

IMPACT Highlights the inadequacy of English-only bias audits for multilingual LLM deployment, necessitating new evaluation strategies.

RANK_REASON Research paper analyzing bias in LLMs across languages. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLMs show transformed, not transferred, bias across English and Swahili

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Research paper analyzing bias in LLMs across languages. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Ruolei Zhang, Teddy Njuguna, Yue Feng ·

    Cross-Lingual Bias in Large Language Models: A Comparative Analysis of English and Swahili

    arXiv:2608.03532v1 Announce Type: new Abstract: Large language models are increasingly deployed in multilingual contexts, yet safety alignment and bias evaluation remain overwhelmingly English-centric. We investigate whether social biases generalise across languages by submitting…

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