Investigating the Impact of Learner Errors on Social Bias in Large Language Models
A controlled framework that injects common learner errors into prompts and applies it to three bias benchmarks covering stereotype alignment and demographic preference across gender, race, and religion finds that grammatical errors increase bias, and the effect grows with the error rate.
Federico Marcuzzi, Martin Christoph, Iryna Gurevych et al.
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