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Back to the Drawing Board for Fair Representation Learning
The evaluation of FRL methods in many recent works primarily focuses on the tradeoff between downstream fairness and accuracy with respect to a single task that was used to approximate the utility of representations during training (proxy task).
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models
Third, we introduce the task of geo-localization as a novel evaluation metric to assess cultural diversity in VLMs.
Factorizers for Distributed Sparse Block Codes
Secondly, the proposed factorizer maintains a high accuracy when queried by noisy product vectors generated using deep convolutional neural networks (CNNs).
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