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cs.CV2026
ES-VP : Energy-Shaped Dynamic Visual Prompting for Efficient Model Adaptation
Can Jin, Ying Li, Jingchen Sun +5
Visual prompting (VP) has emerged as a parameter-efficient method for adapting pre-trained models to downstream tasks. However, existing approaches encounter a trade-off between fl…
cs.CV2026
Uncertainty-Aware Knowledge Distillation for Multimodal Large Language Models
Jingchen Sun, Shaobo Han, Deep Patel +3
Knowledge distillation establishes a learning paradigm that leverages both data supervision and teacher guidance. However, determining the optimal balance between learning from dat…
cs.CV2025
LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation
Can Jin, Ying Li, Mingyu Zhao +6
Visual prompting has gained popularity as a method for adapting pre-trained models to specific tasks, particularly in the realm of parameter-efficient tuning. However, existing vis…