Uniformity Preserving Transfer for Visual Prompt Tuning under Long-tailed Distribution

Key Points

• Improved model generalization is achieved with uniformity preserving transfer under long-tailed distribution.
• The proposed method effectively addresses the challenges posed by imbalanced data sets.
• Analysis incorporates advanced algorithms to enhance visual prompt tuning performance.
• Finding supports the need for innovative approaches to tackle long-tailed data distributions.