arXiv AI September 7, 2026 By Jiangang Zhu, Zheng Wang, Bin Zhu, Yi-Ping Phoebe Chen, Jingjing Chen

VICAL: Vicinal Consistency Alignment for Long-Tailed Visual Recognition

VICAL is a framework for long‑tailed visual recognition that focuses on reducing prediction variance rather than increasing expert diversity. It combines Self‑Consistency Learning, which smooths the loss landscape and mitigates overfitting on tail classes, with Deep Ensemble Distillation, which encourages low‑frequency semantic agreement across experts. Experiments on CIFAR‑LT, ImageNet‑LT, and iNaturalist 2018 demonstrate that VICAL consistently outperforms state‑of‑the‑art methods.

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