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Large pre-trained vision-language models (VLMs) reduce the time for developing predictive models for various vision-grounded language downstream tasks by providing rich, adaptable image and text representations.
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Balanced datasets are not enough: Estimating and mitigating gender bias in deep image representations
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Language models are few-shot learners
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How much can clip benefit vision-and-language tasks?
Sheng Shen, Liunian Harold Li, Hao Tan, Mohit Bansal, Anna Rohrbach, Kai-Wei Chang, Zhewei Yao, and Kurt Keutzer · 2021
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Are gender-neutral queries really gender-neutral? mitigating gender bias in image search
Jialu Wang, Yang Liu, and Xin Eric Wang · 2021
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Are gender-neutral queries really gender-neutral? mitigating gender bias in image search
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VLMo: Unified vision-language pre-training with mixture-of-modality-experts
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Flava: A foundational language and vision alignment model
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Revise: A tool for measuring and mitigating bias in visual datasets
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Unbiased graph embedding with biased graph observations
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