Introduces the StyleGender dataset and PixelSGA/MaskSGA metrics showing that text-to-image models amplify gender artifacts present in artistic styles beyond historical baselines.
arXiv preprint arXiv:2304.13855 , year=
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Med-Gemini sets new records on 10 of 14 medical benchmarks including 91.1% on MedQA-USMLE, beats GPT-4V by 44.5% on multimodal tasks, and surpasses humans on medical text summarization.
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Gender Artifacts from Art History to Text-to-Image Generation
Introduces the StyleGender dataset and PixelSGA/MaskSGA metrics showing that text-to-image models amplify gender artifacts present in artistic styles beyond historical baselines.
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Capabilities of Gemini Models in Medicine
Med-Gemini sets new records on 10 of 14 medical benchmarks including 91.1% on MedQA-USMLE, beats GPT-4V by 44.5% on multimodal tasks, and surpasses humans on medical text summarization.