Qifeng Lei

TuckA: Hierarchical Compact Tensor Experts for Efficient Fine-Tuning

Efficiently fine-tuning pre-trained models for downstream tasks is a key challenge in the era of foundation models. Parameter-efficient fine-tuning (PEFT) presents a promising solution, achieving performance comparable to full fine-tuning by updating only a small number of adaptation weights per lay