3 papers
cs.CV2025
ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning
Enhao Zhang, Chaohua Li, Chuanxing Geng +1
Based on the success of large-scale visual foundation models like CLIP in various downstream tasks, this paper initially attempts to explore their impact on Long-Tailed Semi-Superv…
cs.CV2025
Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey
Chaohua Li, Enhao Zhang, Chuanxing Geng +1
Out-of-distribution detection (OOD) is a pivotal task for real-world applications that trains models to identify samples that are distributionally different from the in-distributio…
cs.LG2024
All-around Neural Collapse for Imbalanced Classification
Enhao Zhang, Chaohua Li, Chuanxing Geng +1
Neural Collapse (NC) presents an elegant geometric structure that enables individual activations (features), class means and classifier (weights) vectors to reach \textit{optimal}…