Imbalanced class distribution is an inherent problem in many real-world classification tasks
where the minority class is the class of interest. Many conventional statistical and machine …

Video grounding aims to localize a moment from an untrimmed video for a given textual
query. Existing approaches focus more on the alignment of visual and language stimuli with …

A recent study has shown a phenomenon called neural collapse in that the within-class
means of features and the classifier weight vectors converge to the vertices of a simplex …

Real-world training data usually exhibits long-tailed distribution, where several majority
classes have a significantly larger number of samples than the remaining minority classes …

This paper presents the results of the news translation task, the multilingual low-resource
translation for Indo-European languages, the triangular translation task, and the automatic …

Abstract Current Scene Graph Generation (SGG) methods explore contextual information to
predict relationships among entity pairs. However, due to the diverse visual appearance of …

In real-world scenarios, data tends to exhibit a long-tailed distribution, which increases the
difficulty of training deep networks. In this paper, we propose a novel self-paced knowledge …

Prediction of enzyme kinetic parameters is essential for designing and optimizing enzymes
for various biotechnological and industrial applications, but the limited performance of …

This work considers the category distribution heterogeneity in federated learning. This issue
is due to biased labeling preferences at multiple clients and is a typical setting of data …

Recent years have witnessed the rapid progress of generative adversarial networks (GANs).
However, the success of the GAN models hinges on a large amount of training data. This …