A proposed pipeline shows LLMs introduce detectable race and gender biases when summarizing life narratives, creating potential for representational harm in research.
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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
2026 2verdicts
UNVERDICTED 2representative citing papers
Mid-sized LLMs outperform larger models on fairness in multi-document news summarization, with entity sentiment bias proving hardest to mitigate across prompt and judge-based interventions.
citing papers explorer
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Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives
A proposed pipeline shows LLMs introduce detectable race and gender biases when summarizing life narratives, creating potential for representational harm in research.
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When Bigger Isn't Better: A Comprehensive Fairness Evaluation of Political Bias in Multi-News Summarisation
Mid-sized LLMs outperform larger models on fairness in multi-document news summarization, with entity sentiment bias proving hardest to mitigate across prompt and judge-based interventions.