Zhenpeng Chen

Mitigating medical bias in large language models by prompt engineering: an empirical study of effectiveness and trade-offs.

Five widely used prompting strategies across five influential LLMs in the latest medical bias benchmark reveal substantial heterogeneity in both effectiveness and overhead across models, with no strategy proving universally effective and some even exacerbating bias.