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Found 4 papers, 2 papers with code
Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation
In this survey, we review prior studies on dimensions of bias: Gender, Skintone, and Geo-Culture.
Learning to Detect Noisy Labels Using Model-Based Features
Label noise is ubiquitous in various machine learning scenarios such as self-labeling with model predictions and erroneous data annotation.
A Universal Discriminator for Zero-Shot Generalization
In the finetuning setting, our approach also achieves new state-of-the-art results on a wide range of NLP tasks, with only 1/4 parameters of previous methods.
HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting
Based on the homophily assumption of GNN, we propose a homophily-aware constraint to regularize the optimization of the region graph so that neighboring region nodes on the learned graph share similar crime patterns, thus fitting the mechanism of diffusion convolution.
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