imbalanced-classification

This paper proposes BS-cRT, a two-stage baseline for long-tailed recognition that trains a backbone with Balanced Softmax and then retrains only the classifier on balanced batches, achieving consistent few-shot accuracy improvements on multiple benchmarks.

RUBRIC is a generator-agnostic filtering framework for imbalanced classification that selects synthetic samples by balancing realism (via a discriminator) and utility (margin-based scoring), improving F1-macro and recall on benchmarks like credit-card fraud detection.