2 papers
cs.LG2025
Memory-Efficient Fine-Tuning via Low-Rank Activation Compression
Jiang-Xin Shi, Wen-Da Wei, Jin-Fei Qi +3
The parameter-efficient fine-tuning paradigm has garnered significant attention with the advancement of foundation models. Although numerous methods have been proposed to reduce th…
cs.CV2025
LIFT+: Lightweight Fine-Tuning for Long-Tail Learning
Jiang-Xin Shi, Tong Wei, Yu-Feng Li
The fine-tuning paradigm has emerged as a prominent approach for addressing long-tail learning tasks in the era of foundation models. However, the impact of fine-tuning strategies…