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Found 5 papers, 3 papers with code
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations
Our work highlights the importance of understanding the nonlinear effects of model improvement on performance in different subpopulations, and has the potential to inform the development of more equitable and responsible machine learning models.
GPT detectors are biased against non-native English writers
In this study, we evaluate the performance of several widely-used GPT detectors using writing samples from native and non-native English writers.
Learning Graph Neural Networks for Image Style Transfer
To this end, we develop an elaborated GNN model with content and style local patches as the graph vertices.
Safe Distillation Box
In other words, all users may employ a model in SDB for inference, but only authorized users get access to KD from the model.
Mutual-Complementing Framework for Nuclei Detection and Segmentation in Pathology Image
The existing two unsupervised methods are prone to failure on degenerated samples.
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