A well-trained deep neural network on balanced datasets usually exhibits the Neural
Collapse (NC) phenomenon, which is an informative indicator of the model achieving good …

This paper proposes a new pipeline for long-tail (LT) recognition. Instead of re-weighting or
re-sampling, we utilize the long-tailed dataset itself to generate a balanced proxy that can be …

Quality Assurance (QA) aims to prevent mistakes and defects in manufactured products and
avoid problems when delivering products or services to customers. QA for AI systems …

Logit adjustment is an effective long-tailed visual recognition strategy to encourage a
significant margin between rare and dominant labels. Existing methods typically employ the …

Data augmentation for minority classes is an effective strategy for long-tailed recognition,
thus developing a large number of methods. Although these methods all ensure the balance …

Long-tailed recognition (LTR) aims to learn balanced models from extremely unbalanced
training data. Fine-tuning pretrained foundation models has recently emerged as a …

Neural Collapse (NC) presents an elegant geometric structure that enables individual
activations (features), class means and classifier (weights) vectors to reach\textit {optimal} …

Recent advancements in computer vision enable machines to perform tasks like image
classification, object detection, and instance segmentation with high performance. However …

In class-imbalanced learning, the scarcity of information about minority classes presents
challenges in obtaining generalizable features for these classes. Leveraging large-scale pre …

Conformal prediction (CP) has emerged as a rigorous means of providing deep learning
models with reliable uncertainty estimates and safety guarantees. However, its performance …