2026
Parameters as Experts: Adapting Vision Models with Dynamic Parameter Routing for Dense Predictions
ICML 2026poster
Adapting pre-trained vision models using parameter-efficient fine-tuning (PEFT) remains challenging, as it aims to achieve performance comparable to full fine-tuning using a minimal number of trainable parameters. When applied to complex dense prediction tasks, existing methods exhibit limitations, …